Identify-Conceptualize-Align: A Schema-Adaptive Framework for Unified Entity Recognition and Event Detection

Incentivizing Agentic Reasoning Capability with Outcome Supervision for Knowledge Base Question Answering

ConNR: A continual N-ary knowledge reasoner for growing N-ary knowledge graphs

Towards Robust Universal Information Extraction: Dataset, Evaluation, and Solution

Large Language Model-Based Event Relation Extraction with Rationales

Inductive Link Prediction in N-ary Knowledge Graphs

Towards Event Extraction with Massive Types: LLM-based Collaborative Annotation and Partitioning Extraction

A Survey of Link Prediction in N-ary Knowledge Graphs

KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction

Look Globally and Reason: Two-stage Path Reasoning over Sparse Knowledge Graphs

Autonomous Reasoning-Retrieval for Large Language Model Based Recommendation

Bridging Textual-Collaborative Gap through Semantic Codes for Sequential Recommendation

Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation

Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation

Generative Recommender with End-to-End Learnable Item Tokenization

Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation

Reciprocal Sequential Recommendation

Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems

Enhancing Multi-Behavior Sequential Recommenders with Behavior-Aware Regularization

Towards Accurate Distance Estimation for Distribution-Aware c-ANN Search

Understanding the Effect of Loss Functions on the Generalization of Recommendations

Dual Test-Time Training for Out-of-Distribution Recommender System

Automated Sparse and Low-Rank Shallow Autoencoders for Recommendation

Learning to Hash for Trajectory Similarity Computation and Search

Task Recommendation in Spatial Crowdsourcing: A Trade-Off Between Diversity and Coverage

Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation

When large language models meet personalization: perspectives of challenges and opportunities

An Incremental Update Framework for Online Recommenders with Data-Driven Prior

Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute

CR-TKGQA: A Temporal Knowledge Graph Question Answering Dataset Involving Complex Reasoning

SQA: SPARQL Query Annotating with Question-Answer Pairs

TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data

Timeline-based Sentence Decomposition with In Context Learning for Temporal Fact Extraction

QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback based Self-Correction

Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval

Position-Aware Relational Transformer for Knowledge Graph Embedding

PaTeCon: A Pattern-Based Temporal Constraint Mining Method for Conflict Detection on Knowledge Graphs

Question Decomposition Tree for Answering Complex Questions over Knowledge Bases

Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs

Explicit v.s. Implicit Memory: Exploring Multi-hop Complex Reasoning Over Personalized Information

AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignment

LLM Personalization: Foundations, Breakthroughs, and Frontiers

Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation

Online Iterative Self-Alignment for Radiology Report Generation

International Workshop on Multimodal Generative Search and Recommendation (MMGenSR@CIKM 2025)

Latent Inter-User Difference Modeling for LLM Personalization

Online Preference Alignment for Language Models via Count-based Exploration

Task-Agnostic Pre-training and Task-Guided Fine-tuning for Versatile Diffusion Planner

RRM: Robust Reward Model Training Mitigates Reward Hacking

Building Math Agents with Multi-Turn Iterative Preference Learning

Inference Scaling for Long-Context Retrieval Augmented Generation

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective

LiPO: Listwise Preference Optimization through Learning-to-Rank

Hybrid Latent Reasoning via Reinforcement Learning

Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation

Optimizing Compound Retrieval Systems

Predicting Text Preference Via Structured Comparative Reasoning

Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning

Plan Then Retrieve: Reinforcement Learning-Guided Complex Reasoning over Knowledge Graphs

Filter-then-Generate: Large Language Models with Structure-Text Adapter for Knowledge Graph Completion

Enhanced Expert Merging for Mixture-of-Experts in Graph Foundation Models

MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis

Boosting Pre-trained Language Models for Temporal Knowledge Graph Reasoning via Joint Structure and Recurring Patterns

SymAgent: A Neural-Symbolic Self-Learning Agent Framework for Complex Reasoning over Knowledge Graphs

Historical facts learning from Long-Short Terms with Language Model for Temporal Knowledge Graph Reasoning

Clarified Aggregation and Predictive Modeling (CAPM): High-Interpretability Framework for Inductive Link Prediction

UniLP: Unified Topology-aware Generative Framework for Link Prediction in Knowledge Graph

Neighboring relation enhanced inductive knowledge graph link prediction via meta-learning

ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning

Continuous-time Discrete-space Diffusion Model for Recommendation

Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs

Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation

Towards Retrieval-Augmented Large Language Models: Data Management and System Design

Tree-of-AdEditor: Heuristic Tree Reasoning for Automated Video Advertisement Editing with Large Language Model

Graph Machine Learning in the Era of Large Language Models (LLMs)

Score-Based Generative Diffusion Models for Social Recommendations

Multi-Agent Attacks for Black-Box Social Recommendations

A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging

Mitigating Fine-tuning Bias: A Parameter-Efficient Debiasing Framework for Large Language Models

Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective

DA-DAN: A Dual Adversarial Domain Adaption Network for Unsupervised Non-overlapping Cross-domain Recommendation

MCRPL: A Pretrain, Prompt, and Fine-tune Paradigm for Non-overlapping Many-to-one Cross-domain Recommendation

Suit the Remedy to the Retriever: Interpretable Query Optimization with Retriever Preference Alignment for Vision-Language Retrieval

Length-Adaptive Interest Network for Balancing Long and Short Sequence Modeling in CTR Prediction

FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction

Learning Multi-aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation

FairFS: Addressing Deep Feature Selection Biases for Recommender System

Improving Music Recommendation With Fine-Grained Content-Based Behavior Retrieval

UNGER: Generative Recommendation with A Unified Code via Semantic and Collaborative Integration

Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models

EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models

CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling

Large Language Model Can Interpret Latent Space of Sequential Recommender

FreeControl: Efficient, Training-Free Structural Control via One-Step Attention Extraction

Navigating Large Language Models for Recommendation: From Architecture to Learning Paradigms and Deployment

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation

Fair Recommendation with Biased-Limited Sensitive Attribute

CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Learnable Item Tokenization for Generative Recommendation

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models

GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation

The Future of Personalized Universal Assistant

PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation

EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration

Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems

Reward Shaping for User Satisfaction

Balancing Fine-tuning and RAG: A Hybrid Strategy for Dynamic LLM Recommendation Updates

Cross-Batch Aggregation for Streaming Learning from Label Proportions in Industrial-Scale Recommendation Systems

Large Language Models as Analogical Reasoners

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation

Who You Are Matters: Bridging Interests and Social Roles via LLM-Enhanced Logic Recommendation

Enhancing Online Video Recommendation via a Coarse-to-fine Dynamic Uplift Modeling Framework

Generative Recommender with End-to-End Learnable Item Tokenization

Comprehensive List Generation for Multi-Generator Reranking

Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation

Value Function Decomposition in Markov Recommendation Process

AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems

A Self-Adaptive Fairness Constraint Framework for Industrial Recommender System

VPN: Visual Prompt Navigation

Efficient Thought Space Exploration Through Strategic Intervention

AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization

ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability

Retain to Refine: Adaptive Online Question Answering via Query Routing and Long-Short Memory

Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search

ReflectRAG: Enhancing retrieval-augmented generation with GRPO-optimized iterative reflection

S$^{3}$PRank: Toward Satisfaction-Oriented Learning to Rank With Semi-Supervised Pre-Training

FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding

R2GCurL: Reinforced Robust Knowledge Tracing via Dynamic Graph Curriculum Learning

Inference Scaling for Long-Context Retrieval Augmented Generation

Optimizing Compound Retrieval Systems

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing

Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I

Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?

Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance

RD-Suite: A Benchmark for Ranking Distillation

RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses

Rax: Composable Learning-to-Rank Using JAX

On Optimizing Top-K Metrics for Neural Ranking Models

VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents

Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge

Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs

Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments

AgentBench: Evaluating LLMs as Agents

A Branching Decoder for Set Generation

HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models

Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments

Few-shot In-context Learning on Knowledge Base Question Answering

Mind2Web: Towards a Generalist Agent for the Web

RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation

WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging

VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models

Decoupling and Reconstructing: A Multimodal Sentiment Analysis Framework Towards Robustness

TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation

InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models

Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective

Fair Personalized Learner Modeling Without Sensitive Attributes

Unified Representation Learning for Discrete Attribute Enhanced Completely Cold-Start Recommendation

Pre-training General User Representation with Multi-type APP Behaviors

REG4Rec: Reasoning-Enhanced Generative Model for Large-Scale Recommendation Systems

RCLRec: Reverse Curriculum Learning for Modeling Sparse Conversions in Generative Recommendation

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation

HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval

ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems

Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval

Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs

FuXi-γ: Efficient Sequential Recommendation with Exponential-Power Temporal Encoder and Diagonal-Sparse Positional Mechanism

Exploring Recommender System Evaluation: A Multi-Modal LLM Agent Framework for A/B Testing

Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery

A Survey of Personalization: From RAG to Agent

EENet: An Efficient and Effective Network for Large-Scale CTR Prediction

Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark

SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems

Prompt Tuning as User Inherent Profile Inference Machine

KLAN: Kuaishou Landing-page Adaptive Navigator

Heterogeneous Multi-treatment Uplift Modeling for Trade-off Optimization in Short-Video Recommendation

LLM-Powered User Simulator for Recommender System

Stratified Expert Cloning for Retention-Aware Recommendation at Scale

Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation

Who You Are Matters: Bridging Interests and Social Roles via LLM-Enhanced Logic Recommendation

Enhancing Online Video Recommendation via a Coarse-to-fine Dynamic Uplift Modeling Framework

LANCE: Exploration and Reflection for LLM-based Textual Attacks on News Recommender Systems

Comprehensive List Generation for Multi-Generator Reranking

DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems

Associating cognitive abilities with naturalistic search behavior

Incorporating Cognitive Abilities into Web Search Re-ranking

Entity Footprinting: Modeling Contextual User States via Digital Activity Monitoring

Naturalistic Digital Behavior Predicts Cognitive Abilities

Predicting Representations of Information Needs from Digital Activity Context

Does More Context Help? Effects of Context Window and Application Source on Retrieval Performance

EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations

Interactive Visual Facets to Support Fluid Exploratory Search

Entity Recommendation for Everyday Digital Tasks

Spoken Conversational Context Improves Query Auto-completion in Web Search

VPN: Visual Prompt Navigation

Efficient Thought Space Exploration Through Strategic Intervention

AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning

Beyond Step Pruning: Information Theory Based Step-level Optimization for Self-Refining Large Language Models

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching

Reinforced Efficient Reasoning via Semantically Diverse Exploration

LLM-Based Listwise Reranking Under the Effect of Positional Bias

Retain to Refine: Adaptive Online Question Answering via Query Routing and Long-Short Memory

VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context Videos

Simulating Dispute Mediation with LLM-Based Agents for Legal Research

Auto-PRE: An Automatic and Cost-Efficient Peer-Review Framework for Language Generation Evaluation

Investigating Prosocial Behavior Theory in LLM Agents Under Policy-Induced Inequities

Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs

Unsupervised Dense Retrieval with Conterfactual Contrastive Learning

Generalized Pseudo-Relevance Feedback

Hierarchical Document-Aware Interest Profiling in Personalized Search

DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task

CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges

RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation

Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Simulation

Diversification as Risk Minimization

OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG

Open-Source LLM-based Relevance Assessment vs. Highly Reliable Manual Relevance Assessment: A Case Study

Reconstruction of 3D Brain Structures from Clinical 2D MRI Data

My System Is As Effective As Yours: Reproducibility, Sustainability, and More

LLM-Assisted Relevance Assessments: When Should We Ask LLMs for Help?

Decoy Effect in Search Interaction: Understanding User Behavior and Measuring System Vulnerability

ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrieval

ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models

LLM-Grounded Diffusion for Cross-Domain Recommendation

Enhancing Cross-Domain Recommendation with Plug-In Contrastive Representations from Large Language Models

Review-Enhanced Hierarchical Contrastive Learning for Recommendation

Contrastive Self-supervised Learning in Recommender Systems: A Survey

Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation

Contrastive Multi-view Interest Learning for Cross-domain Sequential Recommendation

Disentangled Contrastive Learning for Cross-Domain Recommendation

Rating-Review Graph Contrastive Learning for Review-based Recommendation

A Preference Learning Decoupling Framework for User Cold-Start Recommendation

Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation

GNN Explainers 2.0: User-centric and Data-driven Insights

SliceGX: Layer-wise GNN Explanation with Model-slicing

Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search

Self-Supervised Similar Community Search Based on Graph Matching Network

Efficient graph embedding at scale: optimizing CPU-GPU-SSD integration

HC-SpMM: Accelerating Sparse Matrix-Matrix Multiplication for Graphs with Hybrid GPU Cores

Spectral Subspace Clustering for Attributed Graphs

Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities

Stitching Inner Product and Euclidean Metrics for Topology-aware Maximum Inner Product Search

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration

Not All Transparency Is Equal: Source Presentation Effects on Attention, Interaction, and Persuasion in Conversational Search

Improving Data Reusability in Interactive IR: Insights from the Community

Mitigating the Threshold Priming Effect in Large Language Model-Based Relevance Judgments via Personality Simulation

TRUE: A Reproducible Framework for LLM-Driven Relevance Judgment in Information Retrieval

Boundedly Rational Searchers Interacting with Medical Misinformation: Characterizing Context-Dependent Decoy Effects on Credibility and Usefulness Evaluation in Sessions

LLM-Driven Usefulness Labeling for IR Evaluation

IWILDS'25: The 5th International Workshop on Investigating Learning During Web Search

The landscape of data reuse in interactive information retrieval: Motivations, sources, and evaluation of reusability

Falling behind again? Characterizing and assessing older adults' algorithm literacy in interactions with video recommendations

Decoy Effect in Search Interaction: Understanding User Behavior and Measuring System Vulnerability

COLUMBUS: Evaluating COgnitive Lateral Understanding Through Multiple-Choice reBUSes

OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization

WebEvolver: Enhancing Web Agent Self-Improvement with Co-evolving World Model

Retrieval-augmented GUI Agents with Generative Guidelines

DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?

RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph

WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models

Dense X Retrieval: What Retrieval Granularity Should We Use?

MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning

Practical, Efficient, In-Memory Inverted Indexes

Scalable K-Means Guided Partitioning for Block-based Sparse Document Retrieval

E2Rank: Efficient and Effective Layer-Wise Reranking

ColBERT-Serve: Efficient Multi-stage Memory-Mapped Scoring

Efficient Constant-Space Multi-vector Retrieval

Unveiling DIME: Reproducibility, Generalizability, and Formal Analysis of Dimension Importance Estimation for Dense Retrieval

Fast and Effective Early Termination for Simple Ranking Functions

Efficient In-Memory Inverted Indexes: Theory and Practice

A Flexible Resource for Top-Weighted Comparisons Between Sets and Rankings

Improved Learned Sparse Retrieval with Corpus-Specific Vocabularies

Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning

FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs

Crocodile: Cross Experts Covariance for Disentangled Learning in Multi-Domain Recommendation

Incremental Learning for LLM-based Tokenization and Recommendation

Long-Sequence Recommendation Models Need Decoupled Embeddings

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models

Towards Unifying Feature Interaction Models for Click-Through Rate Prediction

Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models

STEM: Unleashing the Power of Embeddings for Multi-Task Recommendation

Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs

Navigating Through Paper Flood: Advancing LLM-Based Paper Evaluation Through Domain-Aware Retrieval and Latent Reasoning

MGFRec: Towards Reinforced Reasoning Recommendation with Multiple Groundings and Feedback

PFMAR: A multi-agent conversational recommender system for high-involvement products

Tunable LLM-based Proactive Recommendation Agent

An LLM-based Behavior Modeling Framework for Malicious User Detection

Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response

Fine-grained List-wise Alignment for Generative Medication Recommendation

Large Language Models with Multi-faceted Relation Alignment for User Novel Interest Discovery

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation

G-SAN: Rethinking Audio Navigation Beyond Time in Podcasts

Hidden Labor behind the Hype: Understanding AI Side Hustles through Platform Narratives and Worker Practices

AITQE: An Adaptive Image-Text Quality Enhancer for Scalable MLLM Pretraining

LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation

CFBench: A Comprehensive Constraints-Following Benchmark for LLMs

RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation

Improving Accuracy and Calibration via Differentiated Deep Mutual Learning

Efficient Motion-Aware Video MLLM

Beyond Sight: Towards Cognitive Alignment in LVLM via Enriched Visual Knowledge

Extracting and Combining Abilities For Building Multi-lingual Ability-enhanced Large Language Models

Understanding the User: An Intent-Based Ranking Dataset

Data Augmentation for Sample Efficient and Robust Document Ranking

Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders

Extractive Explanations for Interpretable Text Ranking

Efficient Neural Ranking using Forward Indexes

Node Representation Learning for Directed Graphs

Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF

LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts

Dodo: Dynamic Contextual Compression for Decoder-only LMs

Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories

Axiomatic Preference Modeling for Longform Question Answering

Zero-shot Clarifying Question Generation for Conversational Search

Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention

Contextual Re-Ranking with Behavior Aware Transformers

An Axiomatic Approach to Regularizing Neural Ranking Models

Generic Intent Representation in Web Search

Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval

Compress-then-Rank: Faster and Better Listwise Reranking with Large Language Models via Ranking-Aware Passage Compression

GeoArena: Evaluating Open-World Geographic Reasoning in Large Vision-Language Models

MTA: A Merge-then-Adapt Framework for Personalized Large Language Models

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Bridging Personalization and AI: From RAG to Agent

Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery

To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention

When coordinated response meets complexity in catastrophes: Unlocking cross-sectoral emergency resource sharing

Split-Merge: Scalable and Memory-Efficient Merging of Expert LLMs

Pairwise Sample Complexity for Fair Active Ranking with Cascaded Norm Objectives

Optimizing Learning-to-Rank Models for Ex-Post Fair Relevance

Increasing Impact of Mobile Health Programs: SAHELI for Maternal and Child Care

Sampling Individually-Fair Rankings that are Always Group Fair

Sampling Ex-Post Group-Fair Rankings

Socially Fair Center-Based and Linear Subspace Clustering

On the Problem of Underranking in Group-Fair Ranking

Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining

CASCADE: Contextual Sarcasm Detection in Online Discussion Forums

TRAWL: External Knowledge-Enhanced Recommendation with LLM Assistance

PRECISE: Pre-training and Fine-tuning Sequential Recommenders with Collaborative and Semantic Information

Personalized Multi Modal Alignment Encoding for CTR-Recommendation in WeChat

Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation

Adaptive Graph Integration for Cross-Domain Recommendation via Heterogeneous Graph Coordinators

MetapathVis: Inspecting the Effect of Metapath in Heterogeneous Network Embedding via Visual Analytics

Exploiting dynamic social feedback for session-based recommendation

Graph Domain Adaptation: A Generative View

Alleviating Video-length Effect for Micro-video Recommendation

Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat

ReFormeR: Learning and Applying Explicit Query Reformulation Patterns

Structure-Aware Pre-retrieval Performance Prediction on Query Affinity Graphs

Can QPP Choose the Right Query variant? Evaluating Query Variant Selection for RAG Pipelines

From Doxa to Logos in Scientific Peer Review

A Reproducibility Study of LLM-Based Query Reformulation

Peerispect: Claim Verification in Scientific Peer Reviews

Failing Forward: Understanding Query Failure in Retrieval, Judgment, and Generation

PeerPrism: Peer Evaluation Expertise vs Review-writing AI

Can LLMs Uphold Research Integrity? Evaluating the Role of LLMs in Peer Review Quality

Query Performance Prediction Using Neural Query Space Proximity

REG4Rec: Reasoning-Enhanced Generative Model for Large-Scale Recommendation Systems

RCLRec: Reverse Curriculum Learning for Modeling Sparse Conversions in Generative Recommendation

Counterfactual Multi-task Learning for Delayed Conversion Modeling in E-commerce Sales Pre-Promotion

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation

Infer As You Train: A Symmetric Paradigm of Masked Generative for Click-Through Rate Prediction

Global-Distribution Aware Scenario-Specific Variational Representation Learning Framework

Distribution-Guided Auto-Encoder for User Multimodal Interest Cross Fusion

HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval

LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction

AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents

Enhanced Pre-training for Recommendation via Hypergraph Structural Entropy

Collaborative Alignment for Recommendation

Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation

Instruction-based Hypergraph Pretraining

Knowledge Graph Context-Enhanced Diversified Recommendation

Unified Pretraining for Recommendation via Task Hypergraphs

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation

Multi-View Graph Convolution for Participant Recommendation

Graph-based Alignment and Uniformity for Recommendation

Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing

A Survey of Reasoning-Intensive Retrieval: Progress and Challenges

Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems

VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos

LimRank: Less is More for Reasoning-Intensive Information Reranking

IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval

EasyST: A Simple Framework for Spatio-Temporal Prediction

HiGPT: Heterogeneous Graph Language Model

DiffMM: Multi-Modal Diffusion Model for Recommendation

GraphGPT: Graph Instruction Tuning for Large Language Models

SSLRec: A Self-Supervised Learning Framework for Recommendation

LLMRec: Large Language Models with Graph Augmentation for Recommendation

Representation Learning with Large Language Models for Recommendation

PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning

Multi-Relational Contrastive Learning for Recommendation

Heterogeneous Graph Contrastive Learning for Recommendation

QE-RAG: A Robust Retrieval-Augmented Generation Benchmark for Query Entry Errors

When Rules Fall Short: Agent-Driven Discovery of Emerging Content Issues in Short Video Platforms

Disentangled Interest Network for Out-of-Distribution CTR Prediction

Granularity-Adaptive Spatial Evidence Tokenization for Video Question Answering

Trigger3: Refining Query Correction via Adaptive Model Selector

Following the Autoregressive Nature of LLM Embeddings via Compression and Alignment

Pyramidal Flow Matching for Efficient Video Generative Modeling

Making Transformer Decoders Better Differentiable Indexers

RecFlow: An Industrial Full Flow Recommendation Dataset

ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability

Large Language Model Unlearning for Source Code

DAVSP: Safety Alignment for Large Vision-Language Models via Deep Aligned Visual Safety Prompt

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization

Saber: Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model in Code Generation

CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

KoCo-Bench: Can Large Language Models Leverage Domain Knowledge in Software Development?

Peer-aided repairer: empowering large language models to repair advanced student assignments

PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing

Rethinking Repetition Problems of LLMs in Code Generation

Benchmarking Long-Context Language Models on Long Code Understanding

Learning Multi-aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation

Full Retraining, Incremental Fine-tuning, and Hybrid Serving: Model Updating and Serving for Industrial Generative Recommender Systems

Accelerating Generative Recommendation via Simple Categorical User Sequence Compression

ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation

Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation (Extended Abstract)

Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning

Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation

Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation

EasyGen: Easing Multimodal Generation with BiDiffuser and LLMs

DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens

Generative Auto-bidding via Conditional Diffusion Modeling

AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games

Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding

Sustainable Online Reinforcement Learning for Auto-bidding

LLM-Powered User Simulator for Recommender System

KINDLE: Knowledge-Guided Distillation for Prior-Free Gene Regulatory Network Inference

Modeling User Retention through Generative Flow Networks

Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention

M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework

Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation

AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation

Learning Empirical Bregman Divergence for Uncertain Distance Representation

KuaiSim: A Comprehensive Simulator for Recommender Systems

Multi-Task Recommendations with Reinforcement Learning

Unconstrained Monotonic Calibration of Predictions in Deep Ranking Systems

Recommendation Unlearning via Influence Function

GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting

LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting

Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework

Inductive Generative Recommendation via Retrieval-based Speculation

Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Deriving Character Logic from Storyline as Codified Decision Trees

A Survey of Large Language Models

Erratum: Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

Towards Large Generative Recommendation: A Tokenization Perspective

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation

Generating Long Semantic IDs in Parallel for Recommendation

Unlocking Decoding-time Controllability: Gradient-Free Multi-Objective Alignment with Contrastive Prompts

Review-Enhanced Universal Sequence Representation Learning for Recommender Systems

Delayed Feedback Modeling with Influence Functions

DynamicPO: Dynamic Preference Optimization for Recommendation

Invariant graph learning meets information bottleneck for out-of-distribution generalization

AdViP: Aligning Multi-modal LLMs via Adaptive Vision-enhanced Preference Optimization

Large Language Model Can Interpret Latent Space of Sequential Recommender

Personal Travel Solver: A Preference-Driven LLM-Solver System for Travel Planning

Towards Large Generative Recommendation: A Tokenization Perspective

Unified Parameter-Efficient Unlearning for LLMs

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization

Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?

FARM: Frequency-Aware Model for Cross-Domain Live-Streaming Recommendation

OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service

DiffGRM: Diffusion-based Generative Recommendation Model

GRank: Towards Target-Aware and Streamlined Industrial Retrieval with a Generate-Rank Framework

MISS: Multi-Modal Tree Indexing and Searching with Lifelong Sequential Behavior for Retrieval Recommendation

MPFormer: Adaptive Framework for Industrial Multi-Task Personalized Sequential Retriever

FIM: Frequency-Aware Multi-View Interest Modeling for Local-Life Service Recommendation

One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction

Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval

MTA: A Merge-then-Adapt Framework for Personalized Large Language Models

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Exploring Recommender System Evaluation: A Multi-Modal LLM Agent Framework for A/B Testing

Bridging Personalization and AI: From RAG to Agent

Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery

NEZHA: A Zero-sacrifice and Hyperspeed Decoding Architecture for Generative Recommendations

To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention

A Survey of Personalization: From RAG to Agent

FARM: Frequency-Aware Model for Cross-Domain Live-Streaming Recommendation

From Agnostic to Specific: Latent Preference Diffusion for Multi-Behavior Sequential Recommendation

PushGen: Push Notifications Generation with LLM

Foresight Prediction Enhanced Live-Streaming Recommendation

ChorusCVR: Chorus Supervision for Entire Space Post-Click Conversion Rate Modeling

Pantheon: Personalized Multi-objective Ensemble Sort via Iterative Pareto Policy Optimization

QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou

MARM: Unlocking the Recommendation Cache Scaling-Law through Memory Augmentation and Scalable Complexity

Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users

HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou

UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities

Efficient Long Context Language Model Retrieval with Compression

Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Database-Augmented Query Representation for Information Retrieval

Efficient Real-time Refinement of Language Model Text Generation

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models

System Prompt Optimization with Meta-Learning

An Empirical Study of Multilingual Reasoning Distillation for Question Answering

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

BrowseComp-Plus: A Fair and Disentangled Evaluation Benchmark for Deep Search Agents

Do We Still Need Text Features for Video Retrieval in the Era of Vision-Language Models?

[inline-graphic not available: see fulltext] Starbucks: Improved Training for 2D Matryoshka Embeddings

Where Relevance Emerges: A Layer-Wise Study of Internal Attention for Zero-Shot Re-Ranking

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning

Layer-wise Token Compression for Efficient Document Reranking

VISA: Retrieval Augmented Generation with Visual Source Attribution

The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It

Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora

TEC: A Collection of Human Trial-and-error Trajectories for Problem Solving

Dynamic and Parametric Retrieval-Augmented Generation

Combining Multiple Supervision for Robust Zero-Shot Dense Retrieval

Prompt Refinement with Image Pivot for Text-to-Image Generation

Query Augmentation with Brain Signals

Scaling Laws For Dense Retrieval

Capability-aware Prompt Reformulation Learning for Text-to-Image Generation

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract)

Constructing Tree-based Index for Efficient and Effective Dense Retrieval

Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

RecLM: Recommendation Instruction Tuning

RecGPT: A Foundation Model for Sequential Recommendation

GraphAgent: Agentic Graph Language Assistant

AI-Researcher: Autonomous Scientific Innovation

Pre-training for Recommendation Unlearning

Collaborative Diffusion Models for Recommendation

LightGNN: Simple Graph Neural Network for Recommendation

DiffGraph: Heterogeneous Graph Diffusion Model

MixRec: Heterogeneous Graph Collaborative Filtering

Urban Computing in the Era of Large Language Models

Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection

On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective

A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems

LODENet: A Holistic Approach to Offline Handwritten Chinese and Japanese Text Line Recognition

Masking in Multi-hop QA: An Analysis of How Language Models Perform with Context Permutation

Prompting large language models with knowledge graphs for question answering involving long-tail facts

A Large-scale Offer Alignment Model for Partitioning Filtering and Matching Product Offers

Retrieval Augmented Generation with Rich Answer Encoding

Information Farming: From Berry Picking to Berry Growing

The Third Search Futures Workshop at ECIR'26

Assessing Risks in Online Information Sharing

Search Changes Consumers' Minds: How Recognizing Gaps Drives Sustainable Choices: How Recognizing Gaps Drives Sustainable Choices

Improving the Reusability of Conversational Search Test Collections

Conversational Gold: Evaluating Personalized Conversational Search System Using Gold Nuggets

From Query to Conscience: The Importance of Information Retrieval in Empowering Socially Responsible Consumerism

Search under Uncertainty: Cognitive Biases and Heuristics - Tutorial on Modeling Search Interaction using Behavioral Economics

Seeking Socially Responsible Consumers: Exploring the Intention-Search-Behaviour Gap

The Influence of Presentation and Performance on User Satisfaction

LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations

The KoLMogorov Test: Compression by Code Generation

AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?

Making Retrieval-Augmented Language Models Robust to Irrelevant Context

Evaluating the Ripple Effects of Knowledge Editing in Language Models

Answering Questions by Meta-Reasoning over Multiple Chains of Thought

Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills

SCROLLS: Standardized CompaRison Over Long Language Sequences

MultiModalQA: complex question answering over text, tables and images

ConsistRM: Improving Generative Reward Models via Consistency-Aware Self-Training

ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework

Reinforced Efficient Reasoning via Semantically Diverse Exploration

RAG-Enhanced Large Language Models for Dynamic Content Expiration Prediction in Web Search

Population-Guided Intent-Aware Query Rewriting for Web Search

Accurate and Efficient Personalized Query Rewriting in Baidu Search

Utility-Focused LLM Annotation for Retrieval and Retrieval-Augmented Generation

TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy

MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification

PRADA: Pre-Train Ranking Models With Diverse Relevance Signals Mined From Search Logs

Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding

Rethinking Continual Knowledge Graph Embedding: Benchmarks and Analysis

Logic-Aware Knowledge Graph Reasoning for Structural Sparsity under Large Language Model Supervision

Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond

PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering

Untargeted Adversarial Attack on Knowledge Graph Embeddings

A Symbolic Rule Integration Framework with Logic Transformer for Inductive Relation Prediction

Context-Aware Commonsense Knowledge Graph Reasoning With Path-Guided Explanations

Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-Shot Logical Reasoning Over Text

GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse

ExplainHM++: Explainable Harmful Meme Detection With Retrieval-Augmented Debate Between Large Multimodal Models

A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM

LLM-Enhanced Multiple Instance Learning for Joint Rumor and Stance Detection with Social Context Information

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models

Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom

Towards low-resource rumor detection: Unified contrastive transfer with propagation structure

CoTea: Collaborative teaching for low-resource named entity recognition with a divide-and-conquer strategy

WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom

Towards Fine-Grained Reasoning for Fake News Detection

MiniRAG: A Lightweight RAG system with Small Language Models

VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context Videos

RecGPT: A Foundation Model for Sequential Recommendation

EasyRec: Simple yet Effective Language Models for Recommendation

Urban Computing in the Era of Large Language Models

A Survey of Large Language Models for Graphs

SSLRec: A Self-Supervised Learning Framework for Recommendation

LLMRec: Large Language Models with Graph Augmentation for Recommendation

Representation Learning with Large Language Models for Recommendation

How Expressive are Graph Neural Networks in Recommendation?

Breaking the Relevance-Diversity Seesaw: Hierarchical LLM Reasoning with RL for Industrial Novelty Recommendation

GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation

Hierarchical User Long-term Behavior Modeling for Click-Through Rate Prediction

Gradient Coordination for Quantifying and Maximizing Knowledge Transference in Multi-Task Learning

AdaSparse: Learning Adaptively Sparse Structures for Multi-Domain Click-Through Rate Prediction

Towards Personalized Bundle Creative Generation with Contrastive Non-Autoregressive Decoding

Grow-on-Demand: Sparse and Adaptive Expert Expansion for Continual Instruction Tuning

Beyond Timestamps: Bridging Forward and Backward Reasoning in Temporal Numerical and Relational Understanding

Hyperbolic Multimodal Generative Representation Learning for Generalized Zero-Shot Multimodal Information Extraction

SMIR: Span-based multi-grained information refinement for joint multimodal entity-relation extraction

Dark Side of Modalities: Reinforced Multimodal Distillation for Multimodal Knowledge Graph Reasoning

Multimodal Knowledge Graph Error Detection with Disentanglement VAE and Multi-Grained Triplet Confidence

Multimodal Graph-Based Variational Mixture of Experts Network for Zero-Shot Multimodal Information Extraction

ME3A: A Multimodal Entity Entailment framework for multimodal Entity Alignment

Few-shot temporal knowledge graph completion based on query-adaptive Mamba-enhanced temporal relation learning

Coarse-to-fine multimodal prototype network for few-shot multimodal relation extraction

Learning to Reason for Multi-Step Retrieval of Personal Context in Personalized Question Answering

Enhancing AI Agents with Human Theory of Mind (ToM) for Context-Aware Actions

Mind Over Machine: Evaluating Theory of Mind Reasoning in LLMs and Humans

How Does Memorization Impact LLMs' Social Reasoning? An Assessment using Seen and Unseen Queries

Towards More Personalized Recommendations by Modeling Users? Temporal Behaviors with Task-Based Graph Neural Network (TGNN)

Assessing Human Viewpoints in Theory of Mind for Large Language Models in Open-Ended Questioning

AuditLLM: A Tool for Auditing Large Language Models Using Multiprobe Approach

Can LLMs Reason Like Humans? Assessing Theory of Mind Reasoning in LLMs for Open-Ended Questions

Representing Tasks with a Graph-Based Method for Supporting Users in Complex Search Tasks

From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild

Each Fake News Is Fake in Its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News Detection

IMOL: Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection

How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis

Harmony in Chaos: A Progressive Noise-Resilient Network for Robust Fake News Video Detection

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding

Understand, Refine and Summarize: Multi-View Knowledge Progressive Enhancement Learning for Fake News Video Detection

Bridging Interests and Truth: Towards Mitigating Fake News with Personalized and Truthful Recommendations

Graphing the Truth: Harnessing Causal Insights for Advanced Multimodal Fake News Detection

Event-Radar: Event-driven Multi-View Learning for Multimodal Fake News Detection

MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation

Chain of Execution Supervision Promotes General Reasoning in Large Language Models

Teaching Language Models to Reason with Tools

Navigating Large Language Models for Recommendation: From Architecture to Learning Paradigms and Deployment

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation

Fair Recommendation with Biased-Limited Sensitive Attribute

CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models

Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities

Focal-RegionFace: Generating Fine-Grained Multi-attribute Descriptions for Arbitrarily Selected Face Focal Regions

Beyond efficient fine-tuning: Efficient hybrid fine-tuning of CLIP models guided by explainable ViT attention

Benchmarking Multimodal Large Language Models for missing modality completion in product catalogues

Bridging NIP and MLM: A Unified Meta-Learning Framework for Sequential Recommendation

A Content-Driven Micro-Video Recommendation Dataset at Scale

Frequency-Decoupled Distillation for Efficient Multimodal Recommendation

Video-Bench: Human-Aligned Video Generation Benchmark

Multimodal Representation Learning Techniques for Comprehensive Facial State Analysis

Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering

How Do Graph Signals Affect Recommendation: Unveiling the Mystery of Low and High-Frequency Graph Signals

A General Strategy Graph Collaborative Filtering for Recommendation Unlearning

Meta-Optimized Joint Generative and Contrastive Learning for Sequential Recommendation

Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering

LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning

Learnable Model Augmentation Contrastive Learning for Sequential Recommendation

Multi-dimensional Graph Neural Network for Sequential Recommendation

Edge-enhanced Global Disentangled Graph Neural Network for Sequential Recommendation

Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential Recommendation

Click is not equal to purchase: multi-task reinforcement learning for multi-behavior recommendation

From implicit parameters to explicit knowledge graphs: A structured knowledge recall framework for bidirectional generalization in LLMs

GraphRAG-Induced Dual Knowledge Structure Graphs for Personalized Learning Path Recommendation

Graph-to-Tree: Topological Decomposition for Self-Supervised Learning

Multi-faceted contrastive learning with inter-frame difference for traffic video question answering

ComGRL: Comprehensive Graph Representation Learning From Local to Global Bridged by Mixup

Integrating Entropy Regulation and Dual-Objective Optimization for Personalized Exercise Recommendation

HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation

Decomposing and Revising What Language Models Generate

Equivalence is All: A Unified View for Self-supervised Graph Learning

Progressive Prefix-Memory Tuning for Complex Logical Query Answering on Knowledge Graphs

Results of the Big ANN: NeurIPS'23 competition

An Analysis of Fusion Functions for Hybrid Retrieval

An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors

Bridging Dense and Sparse Maximum Inner Product Search

SDR: Efficient Neural Re-ranking using Succinct Document Representation

IR Evaluation and Learning in the Presence of Forbidden Documents

Compressing Tabular Data via Pairwise Dependencies

A Diagonal-Augmented quasi-Newton method with application to factorization machines

Strong Successive Refinability and Rate-Distortion-Complexity Tradeoff

Compression for Quadratic Similarity Queries: Finite Blocklength and Practical Schemes

GAM: A Generative Auto-Marketing Framework in Online E-commerce Platforms

Marketing Hosting: From Fixed to Endogenous Budgets

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens

Dual Discrepancy-Based Continuation Learning for Hybrid Supervised Multi-View 3D Object Detection

Generative Auto-bidding via Conditional Diffusion Modeling

Evaluation of Text-to-Video Generation Models: A Dynamics Perspective

Large Language Model Can Interpret Latent Space of Sequential Recommender

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization

AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization

On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenders

Addressing Missing Data Issue for Diffusion-based Recommendation

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

On Softmax Direct Preference Optimization for Recommendation

β-DPO: Direct Preference Optimization with Dynamic β

LLaRA: Large Language-Recommendation Assistant

Item-side Fairness of Large Language Model-based Recommendation System

Multi-view Semantic Contrastive Alignment for Multimodal Recommendation

Disentangled Contrastive Bundle Recommendation with Conditional Diffusion

Graph Diffusive Self-Supervised Learning for Social Recommendation

MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning

PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation

HydraRAG: Structured Cross-Source Enhanced Large Language Model Reasoning

Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning

Higher-Order Peak Decomposition

RMBRec: Robust Multi-Behavior Recommendation towards Target Behaviors

Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias

I3-MRec: Invariant Learning with Information Bottleneck for Incomplete Modality Recommendation

Breaking student-concept sparsity barrier for cognitive diagnosis

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias

Multimodality Invariant Learning for Multimedia-Based New Item Recommendation

Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning

Erratum: Lightweight Embeddings with Graph Rewiring for Collaborative Filtering

In-context Learning for Addressing User Cold-start in Sequential Movie Recommenders

Lightweight Embeddings with Graph Rewiring for Collaborative Filtering

Hate Speech Detection with Generalizable Target-aware Fairness

Lightweight Embeddings for Graph Collaborative Filtering

Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation

Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verification

Just What You Desire: Constrained Timeline Summarization with Self-Reflection for Enhanced Relevance

STARE at the Structure: Steering ICL Exemplar Selection with Structural Alignment

Decomposition Dilemmas: Does Claim Decomposition Boost or Burden Fact-Checking Performance?

From Moments to Milestones: Incremental Timeline Summarization Leveraging Large Language Models

Measuring Individual User Fairness with User Similarity and Effectiveness Disparity

Relevance-aware Individual Item Fairness Measures for Recommender Systems: Limitations and Usage Guidelines

Stairway to Fairness: Connecting Group and Individual Fairness

Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier

Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study

Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance

[inline-graphic not available: see fulltext] SuiteEval: Simplifying Retrieval Benchmarks

Optimal Re-Ranking Depth

Towards a Relevance Posterior in Neural Information Access

Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora

MechIR: A Mechanistic Interpretability Framework for Information Retrieval

Large Language Model Relevance Assessors Agree With One Another More Than With Human Assessors

Constructing and Evaluating Declarative RAG Pipelines in PyTerrier

Variations in Relevance Judgments and the Shelf Life of Test Collections

Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models

Axiomatic Guidance for Efficient and Controlled Neural Search

Addressing Personalized Bias for Unbiased Learning to Rank

Distributionally Robust Optimization for Unbiased Learning to Rank

Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study

REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark

Paint by Inpaint: Learning to Add Image Objects by Removing Them First

DocReRank: Single-Page Hard Negative Query Generation for Training Multi-Modal RAG Rerankers

Harmonic Dataset Distillation for Time Series Forecasting

Capturing User Interests from Data Streams for Continual Sequential Recommendation

Continual Collaborative Distillation for Recommender System

From Lab to Reality: An Eye-tracking Study of How Users are Influenced to Search in the Era of GenAI

VulGen: Workshop on Vulnerabilities in Generative Systems for Information Retrieval

A Comparative Analysis of Linguistic and Retrieval Diversity in LLM-Generated Search Queries

What do Users Really Ask Large Language Models? An Initial Log Analysis of Google Bard Interactions in the Wild

Stable and Adaptive Fusion for Multi-domain Multi-task Recommendation

Sharpness-Consistent Cross-Domain Recommendation for Cold-Start Items

Inverse Contrastive Representation Learning for Post-Click Conversion Rate Estimation

Entire-Space Variational Information Exploitation for Post-Click Conversion Rate Prediction

From Detection to Understanding: Multi-Turn Reasoning for Video Misinformation Analysis

From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild

Towards real-world multimodal propagation networks: Multimodal uncertainty graph contrastive learning for fake news detection

Graph Mixture of Experts with Differential Cross-Attention Alignment for Multimodal Intent Recognition

Each Fake News Is Fake in Its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News Detection

IMOL: Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection

Harmony in Chaos: A Progressive Noise-Resilient Network for Robust Fake News Video Detection

Understand, Refine and Summarize: Multi-View Knowledge Progressive Enhancement Learning for Fake News Video Detection

Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection

Bridging Interests and Truth: Towards Mitigating Fake News with Personalized and Truthful Recommendations

ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability

Reinforced Efficient Reasoning via Semantically Diverse Exploration

LLM-Based Listwise Reranking Under the Effect of Positional Bias

Retain to Refine: Adaptive Online Question Answering via Query Routing and Long-Short Memory

DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent

Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search

Model Editing for New Document Integration in Generative Information Retrieval

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models

Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation

Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models

BrowseComp-Plus: A Fair and Disentangled Evaluation Benchmark for Deep Search Agents

Do We Still Need Text Features for Video Retrieval in the Era of Vision-Language Models?

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning

DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers

VISA: Retrieval Augmented Generation with Visual Source Attribution

General-Reasoner: Advancing LLM Reasoning Across All Domains

Gosling Grows Up: Retrieval with Learned Dense and Sparse Representations Using Anserini

Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality

Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks

Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias

Improving Long-tail User CTR Prediction via Hierarchical Distribution Alignment

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias

Double Correction Framework for Denoising Recommendation

Intersectional Two-sided Fairness in Recommendation

Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction

User Perception of Recommendation Explanation: Are Your Explanations What Users Need?

A Survey on the Fairness of Recommender Systems

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA

Collaborative Alignment for Recommendation

Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation

Instruction-based Hypergraph Pretraining

Knowledge Graph Context-Enhanced Diversified Recommendation

Unified Pretraining for Recommendation via Task Hypergraphs

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation

Multi-View Graph Convolution for Participant Recommendation

Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

Counteracting the Delayed Conversions in OCPC with Survival Analysis

Room Matters: Dynamic Room-level Collaboration Information Modeling for Live Streaming Recommendation

A survey of controllable learning: methods and applications in information retrieval

IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History

Enhancing Bandit Algorithms with LLMs for Time-varying User Preferences in Streaming Recommendations

AdaO2B: Adaptive Online to Batch Conversion for Out-of-Distribution Generalization

Trigger3: Refining Query Correction via Adaptive Model Selector

MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation Alignment

Length-Induced Embedding Collapse in PLM-based Models

Retrieve, Rerank, Answer, Experiment: Hands-On IR Research with PyTerrier

Unsupervised Dense Retrieval with Conterfactual Contrastive Learning

Effective Contrastive Weighting for Dense Query Expansion

Reproducibility, Replicability, and Insights into Dense Multi-Representation Retrieval Models: from ColBERT to Col

ColBERT-PRF: Semantic Pseudo-Relevance Feedback for Dense Passage and Document Retrieval

Neural Pseudo-Relevance Feedback Models for Sparse and Dense Retrieval

An Inspection of the Reproducibility and Replicability of TCT-ColBERT

Improving zero-shot retrieval using dense external expansion

RCLRec: Reverse Curriculum Learning for Modeling Sparse Conversions in Generative Recommendation

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation

Infer As You Train: A Symmetric Paradigm of Masked Generative for Click-Through Rate Prediction

Global-Distribution Aware Scenario-Specific Variational Representation Learning Framework

Distribution-Guided Auto-Encoder for User Multimodal Interest Cross Fusion

HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval

LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction

ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems

Scenario-Adaptive Fine-Grained Personalization Network: Tailoring User Behavior Representation to the Scenario Context

VisRet: Visualization Improves Knowledge-Intensive Text-to-Image Retrieval

LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory

On Leveraging Encoder-only Pre-trained Language Models for Effective Keyphrase Generation

The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented Intervention

Synchronous Faithfulness Monitoring for Trustworthy Retrieval-Augmented Generation

Repoformer: Selective Retrieval for Repository-Level Code Completion

Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks

Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Models

Forward Index Compression for Learned Sparse Retrieval

Evaluating the Efficiency and Effectiveness of Learned Sparse Retrieval with the lsr_benchmark

Multivector Reranking in the Era of Strong First-Stage Retrievers

ReNeuIR at SIGIR 2026: The Fifth Workshop on Reaching Efficiency in Neural Information Retrieval

Efficient Multivector Retrieval with Token-Aware Clustering and Hierarchical Indexing

Sparton: Fast and Memory-Efficient Triton Kernel for Learned Sparse Retrieval

Power- and Fragmentation-Aware Online Scheduling for GPU Datacenters

Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets

kANNolo: Sweet and Smooth Approximate k-Nearest Neighbors Search

Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search

Beyond Single-shot Writing: Deep Research Agents are Unreliable at Multi-turn Report Revision

Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning

Query-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking

To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning

Effective Large Language Model Adaptation for Improved Grounding and Citation Generation

LoFiT: Localized Fine-tuning on LLM Representations

EEL: Efficiently Encoding Lattices for Reranking

Assessing Out-of-Domain Language Model Performance from Few Examples

Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting

Forward Index Compression for Learned Sparse Retrieval

Uncovering Visual-Semantic Psycholinguistic Properties from the Distributional Structure of Text Embedding Space

Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets

Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search

ReNeuIR at SIGIR 2025: The Fourth Workshop on Reaching Efficiency in Neural Information Retrieval

Advances in Vector Search

Pairing Clustered Inverted Indexes with κ-NN Graphs for Fast Approximate Retrieval over Learned Sparse Representations

Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations

A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search

An Analysis of Fusion Functions for Hybrid Retrieval

CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization

ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models

Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning

Enhancing Training Data Attribution with Representational Optimization

Replication and Exploration of Generative Retrieval over Dynamic Corpora

TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy

MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter

Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering

Content-Based Collaborative Generation for Recommender Systems

CAFU: Constrained Alignment and Filtered Uniformity for Denoising Recommendation

FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction

ProEx: A Unified Framework Leveraging Large Language Model with Profile Extrapolation for Recommendation

LLM-UP: SIGIR 2026 Workshop on LLM-powered User Profiling for Search and Recommendation

TF4CTR: Twin Focus Framework for CTR Prediction via Adaptive Sample Differentiation

Heterogeneous Adaptive Preference Learning for Recommendation

Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction

Towards Distribution Matching between Collaborative and Language Spaces for Generative Recommendation

Intent Representation Learning with Large Language Model for Recommendation

Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering

Inference Scaling for Long-Context Retrieval Augmented Generation

LiPO: Listwise Preference Optimization through Learning-to-Rank

Optimizing Compound Retrieval Systems

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing

Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I

Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers?

Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance

LibAUC: A Deep Learning Library for X-Risk Optimization

Towards Disentangling Relevance and Bias in Unbiased Learning to Rank

RD-Suite: A Benchmark for Ranking Distillation

Efficient Personalized Reranking with Semi-autoregressive Generation and Online Knowledge Distillation

FuXi-γ: Efficient Sequential Recommendation with Exponential-Power Temporal Encoder and Diagonal-Sparse Positional Mechanism

Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent

Full Retraining, Incremental Fine-tuning, and Hybrid Serving: Model Updating and Serving for Industrial Generative Recommender Systems

Accelerating Generative Recommendation via Simple Categorical User Sequence Compression

Generative Data Transformation: From Mixed to Unified Data

EENet: An Efficient and Effective Network for Large-Scale CTR Prediction

A Universal Framework for Compressing Embeddings in CTR Prediction

Breaking the Bottleneck: User-Specific Optimization and Real-Time Inference Integration for Sequential Recommendation

Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction

GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse

ExplainHM++: Explainable Harmful Meme Detection With Retrieval-Augmented Debate Between Large Multimodal Models

A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM

Unveiling Privacy Risks in LLM Agent Memory

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models

Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom

Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

Siamese Pre-Trained Transformer Encoder for Knowledge Base Completion

Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection

Efficient and Effective In-context Demonstration Selection with Coreset

AgentOCR: Reimagining Agent History via Optical Self-Compression

Experience-driven Multi-turn Reinforcement Learning for GUI Agents

L-CLIPScore: A Lightweight Embedding-Based Captioning Metric for Evaluating and Training

Adaptively Clustering Neighbor Elements for Image-Text Generation

mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding

SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization

mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models

Endowing Visual Reprogramming with Adversarial Robustness

Towards Efficient Online Tuning of VLM Agents via Counterfactual Soft Reinforcement Learning

Beyond Single-shot Writing: Deep Research Agents are Unreliable at Multi-turn Report Revision

A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning

Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems

MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

SportReason: Evaluating Retrieval-Augmented Reasoning across Tables and Text for Sports Question Answering

FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain

LimRank: Less is More for Reasoning-Intensive Information Reranking

Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective

Are Multimodal LLMs Robust Against Adversarial Perturbations? RoMMath: A Systematic Evaluation on Multimodal Math Reasoning

SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks

Confidence-Aware Fine-Tuning of Sequential Recommendation Systems Via Conformal Prediction

Cluster-Aware Item Prompt Learning for Session-Based Recommendation

Collaborative Alignment for Recommendation

Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation

Instruction-based Hypergraph Pretraining

Knowledge Graph Context-Enhanced Diversified Recommendation

Unified Pretraining for Recommendation via Task Hypergraphs

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation

Multi-View Graph Convolution for Participant Recommendation

Graph-based Alignment and Uniformity for Recommendation

PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations

Balancing Fine-tuning and RAG: A Hybrid Strategy for Dynamic LLM Recommendation Updates

Enhancing Online Ranking Systems via Multi-Surface Co-Training for Content Understanding

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views

Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems

Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models

Improving Data Efficiency for Recommenders and LLMs

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations

Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System

Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation

Generative Representational Learning of Foundation Models for Recommendation

EENet: An Efficient and Effective Network for Large-Scale CTR Prediction

CTRL: Connect Collaborative and Language Model for CTR Prediction

Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation

Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval

An Automatic Graph Construction Framework based on Large Language Models for Recommendation

LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models

Action First: Leveraging Preference-Aware Actions for More Effective Decision-Making in Interactive Recommender Systems

Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding

GAM: A Generative Auto-Marketing Framework in Online E-commerce Platforms

Automated Deterministic Auction Design with Objective Decomposition

DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs

Marketing Hosting: From Fixed to Endogenous Budgets

Beyond Advertising: Mechanism Design for Platform-Wide Marketing Service "QuanZhanTui"

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens

Learning against Non-credible Second-Price Auctions

Truthful Bandit Mechanisms for Repeated Two-stage Ad Auctions

Generative Auto-bidding via Conditional Diffusion Modeling

MergeRec: Model Merging for Data-Isolated Cross-Domain Sequential Recommendation

MUFFIN: Mixture of User-Adaptive Frequency Filtering for Sequential Recommendation

LLM-Enhanced Linear Autoencoders for Recommendation

Empowering Retrieval-based Conversational Recommendation with Contrasting User Preferences

Linear Item-Item Models with Neural Knowledge for Session-based Recommendation

Why is Normalization Necessary for Linear Recommenders?

Temporal Linear Item-Item Model for Sequential Recommendation

Toward a Better Understanding of Loss Functions for Collaborative Filtering

uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering

Bilateral Self-unbiased Learning from Biased Implicit Feedback

On the Use of LLMs for Relevance Labelling

Diversification and Fairness in Search: Two Sides of the Same Coin?

Relevance-aware Individual Item Fairness Measures for Recommender Systems: Limitations and Usage Guidelines

A Comparative Analysis of Linguistic and Retrieval Diversity in LLM-Generated Search Queries

Stairway to Fairness: Connecting Group and Individual Fairness

Classifying Term Variants in Query Formulation

The Effects of Demographic Instructions on LLM Personas

Online and Offline Evaluation in Search Clarification

Walert: Putting Conversational Information Seeking Knowledge into Action by Building and Evaluating a Large Language Model-Powered Chatbot

Enhancing Human Annotation: Leveraging Large Language Models and Efficient Batch Processing

A Survey of Large Language Models

Erratum: Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

STARec: An Efficient Agent Framework for Recommender Systems via Autonomous Deliberate Reasoning

A Pre-trained Plug-in Mixture-of-LoRAs Model for Transferable Sequential Recommendation

Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation

Frequency-Augmented Mixture-of-Heterogeneous-Experts Framework for Sequential Recommendation

Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis

Review-Enhanced Universal Sequence Representation Learning for Recommender Systems

Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

Curriculum-scheduled knowledge distillation from multiple pre-trained teachers for multi-domain sequential recommendation

Subspace-Aware Graph Construction and Contrastive Alignment for Multimodal Recommendation with Large Language Models

Hyperbolic-Enhanced Mixture-of-Experts Mamba for Sequential Recommendation

Potent but Stealthy: Rethink Profile Pollution Against Sequential Recommendation via Bi-Level Constrained Reinforcement Paradigm

IdeFN: Identifying Unclicked Space False Negatives via Relaxed Partial Optimal Transport for Conversion Rate Prediction

Joint Similar User Exploration and Informative Behavior Guidance for Multi-Modal New Item Recommendation

Pareto-optimal estimation and policy learning for balancing short-term and long-term outcomes

Cluster-Enhanced Dual Discrete Collaborative Filtering for Efficient Recommendation

Enhancing Diffusion Model with Auxiliary Information Mining-Exploration and Efficient Sampling Mechanism for Sequential Recommendation

DR-VAE: Debiased and Representation-enhanced Variational Autoencoder for Collaborative Recommendation

FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation

PAGER: Proactive Monitoring Agent for Enterprise AI Assistant

Scaling Collaborative Filtering with Multimodal Contrastive Fine-tuning

From Anchors to Answers: A Novel Node Tokenizer for Integrating Graph Structure into Large Language Models

Mitigating Language Confusion through Inference-time Intervention

Flow Matching Based Sequential Recommender Model

Generating Negative Samples for Multi-Modal Recommendation

How Does Topology Bias Distort Message Passing in Graph Recommender? A Dirichlet Energy Perspective

Unbiased Learning-to-Rank Needs Unconfounded Propensity Estimation

Model-based Unbiased Learning to Rank

VCGD: Visual Clue Guided Decoding with Caption Model for Mitigating Hallucination in Multimodal Large Language Models

A Boundary Token Graph for Zero-Shot Relation Triplet Extraction Involving Discontinuous Entities

CamoQuery: Language-Guided Reasoning Camouflaged Object Segmentation

Zero-shot Jianzi Recognition as Structured Visual Information Extraction in Open Compositional Symbolic Systems

ATGL: An Adaptive-Threshold Global Loss for Document-level Relation Extraction

DEBAR: Mitigating Contextual Bias in Cross-Document Relation Extraction via Dual-Stream Decoupling

Dual-modal consistency learning for weakly supervised RGB-D camouflaged object detection with scribble annotations

Temporal householder transformation embedding for temporal knowledge graph completion

Dual reasoning enhanced document-level relation extraction

Probing Relative Interaction and Dynamic Calibration in Multi-modal Entity Alignment

SWaT: Statistical Modeling of Video Watch Time through User Behavior Analysis

Multi-modality meets re-learning: mitigating negative transfer in sequential recommendation

eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data

Intention enhanced mixed attentive model for session-based recommendation

Modeling Sequences as Star Graphs to Address Over-Smoothing in Self-Attentive Sequential Recommendation

HAM: Hybrid Associations Models for Sequential Recommendation (Extended abstract)

M2: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation

$\mathop {\mathtt {HAM}}$HAM: Hybrid Associations Models for Sequential Recommendation

Hybrid collaborative filtering methods for recommending search terms to clinicians

OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion

DPWriter: Reinforcement Learning with Diverse Planning Branching for Creative Writing

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

QE-RAG: A Robust Retrieval-Augmented Generation Benchmark for Query Entry Errors

GRADE: Personalized Multi-Task Fusion via Group-Relative Reinforcement Learning with Adaptive Dirichlet Exploration

DiffusionGS: Generative Search with Query Conditioned Diffusion in Kuaishou

Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce

Generative Regression Based Watch Time Prediction for Short-Video Recommendation

DualGR: Generative Retrieval with Long and Short-Term Interests Modeling

ASR-Enhanced Multimodal Representation Learning for Cross-Domain Product Retrieval

Generalizing Vision-Language Models with Dedicated Prompt Guidance

GANPOI: A multi-factor generative adversarial framework for POI recommendation

Dynamic Bit-Wise Semantic Transformer Hashing for Multi-Modal Retrieval

Unified stable and generalizable online hashing for cross-modal retrieval

Prompt-Driven Bit Extension Hashing for Continual Cross-Modal Retrieval

Training-Free Open-Set Domain Adaptation With Vision-Language Models

PIC-CMH: Efficient Prompt-Infused Continual Cross-Modal Hashing

EffiPOI: A Product Quantization Framework Based on Knowledge Distillation for Efficient POI Recommendations

Noise-Robust Generative Hashing for Cross-Modal Retrieval

Source-free Domain Adaptation with Multiple Alignment for Efficient Image Retrieval

Simulating the Lateral Reader for News Trustworthiness Reports with an Iterative Multi-Agent RAG System

Resources for Automated Evaluation of Assistive RAG Systems that Help Readers with News Trustworthiness Assessment

Extending MovieLens-32M to Provide New Evaluation Objectives

A Preference Judgment Tool for Authoritative Assessment

The Dark Side of Relevance: The Effect of Non-Relevant Results on Search Behavior

Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search

Visualizing Searcher Gaze Patterns

Evaluation Measures Based on Preference Graphs

Assessing Top- Preferences

A Think-Aloud Study to Understand Factors Affecting Online Health Search

Toward Generalized Web Agent Training: A Deep Dive into Entropy-Balanced Reinforcement Learning

DeepAgent: A General Reasoning Agent with Scalable Toolsets

Descriptive and Discriminative Document Identifiers for Generative Retrieval

RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented Generation

Hierarchical Document Refinement for Long-context Retrieval-augmented Generation

RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation

Search-o1: Agentic Search-Enhanced Large Reasoning Models

WebThinker: Empowering Large Reasoning Models with Deep Research Capability

From Matching to Generation: A Survey on Generative Information Retrieval

A Survey of Conversational Search

Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation

Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks

Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection

IAMRec: Intent-Adaptive Multimodal Recommendation with Collaborative-Modality Disentanglement

OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

From Few-Shot to Zero-Shot: Towards Generalist Graph Anomaly Detection

Graph Neural Networks for Graphs With Heterophily: A Survey

A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection

Contrastive Scenario-Aware Meta Prompting for Multi-scenario Recommendation

CASIA-PR-V1: A Multi-Ethnic, Multi-Device and Cross-Spectral Dataset and a Multiscale Disentangled Model for Periocular Recognition

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective

MMLRec: A Unified Multi-Task and Multi-Scenario Learning Benchmark for Recommendation

Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset

MI-DPG: Decomposable Parameter Generation Network Based on Mutual Information for Multi-Scenario Recommendation

SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation

DAE: Distribution-Aware Embedding for Numerical Features in Click-Through Rate Prediction

Global-Aware Model-Free Self-distillation for Recommendation System

Augmenting Intra-Modal Understanding in MLLMs for Robust Multimodal Keyphrase Generation

You Don't Need Pre-Built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structures

LLM Collaborative Filtering: User-Item Graph as New Language

LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoning

LogicPoison: Logical Attacks on Graph Retrieval-Augmented Generation

Knapsack Optimization-Based Schema Linking for LLM-Based Text-to-SQL Generation

Bridging the Topology-Semantic Gap: A Benchmark and Framework for Power Grid Work Ticket Generation

Facilitating Generative Retrieval with Logical Denoising for Interpretable Conversational Search

LoSemB: Logic-Guided Semantic Bridging for Inductive Tool Retrieval

Reliable Reasoning Path: Distilling Effective Guidance for LLM Reasoning With Knowledge Graphs

As It Was: Aligning LLM Search Evaluation with Historical User Preferences

Contextualizing Spotify's Audiobook List Recommendations with Descriptive Shelves

Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge

Semantic IDs for Joint Generative Search and Recommendation

PODTILE: Facilitating Podcast Episode Browsing with Auto-generated Chapters

Bridging Search and Recommendation in Generative Retrieval: Does One Task Help the Other?

Do the Findings of Document and Passage Retrieval Generalize to the Retrieval of Responses for Dialogues?

Improving Content Retrievability in Search with Controllable Query Generation

Pairwise Review-Based Explanations for Voice Product Search

Evaluating the Robustness of Retrieval Pipelines with Query Variation Generators

AutoPP: Towards Automated Product Poster Generation and Optimization

MoFu: Scale-Aware Modulation and Fourier Fusion for Multi-Subject Video Generation

Reasoning-Grounded Intent Injection for Generative Recommendation

DPEO: Dynamic Preference Evolution Optimization for Self-Evolving CTR Prediction

AIPO: Adaptive Anchored Intent-aware Policy Optimization for Generative Recommendation

Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification

A Generative Contextual Comprehension Paradigm for Takeout Ranking Model

Think Then Recommend: An LLM-Powered Multi-Agent Framework for Personalized Conversational Recommender System in E-Commerce

SMTIR: Scenario-Aware Multi-Trigger Induction Network for CTR Prediction

UniERF: A Uniform Embedding-based Retrieval Framework for E-commerce Search

VCGD: Visual Clue Guided Decoding with Caption Model for Mitigating Hallucination in Multimodal Large Language Models

A Boundary Token Graph for Zero-Shot Relation Triplet Extraction Involving Discontinuous Entities

Zero-shot Jianzi Recognition as Structured Visual Information Extraction in Open Compositional Symbolic Systems

ATGL: An Adaptive-Threshold Global Loss for Document-level Relation Extraction

DEBAR: Mitigating Contextual Bias in Cross-Document Relation Extraction via Dual-Stream Decoupling

Dual reasoning enhanced document-level relation extraction

Probing Relative Interaction and Dynamic Calibration in Multi-modal Entity Alignment

RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human Feedback

SGMEA: Structure-Guided Multimodal Entity Alignment

Exploring the Impacts of Feature Fusion Strategy in Multi-modal Entity Alignment

Capturing User Interests from Data Streams for Continual Sequential Recommendation

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation

Continual Recommender Systems

Generalizable Recommender System During Temporal Popularity Distribution Shifts

Embracing Plasticity: Balancing Stability and Plasticity in Continual Recommender Systems

Class-Imbalanced Graph Learning without Class Rebalancing

Ensuring User-side Fairness in Dynamic Recommender Systems

Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding

Directed Network Embedding with Virtual Negative Edges

An Automatic Mobile App Testing Method with User Event Scenario

Scaling LLM Test-Time Compute with Mobile NPU on Smartphones

RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference

LeanK: Learnable K Cache Channel Pruning for Efficient Decoding

SCBench: A KV Cache-Centric Analysis of Long-Context Methods

SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents

MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention

RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval

Chain-of-Model Learning for Language Model

GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents

LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

Déjà Vu of Strange Stickers! Enhancing Out-of-Distribution Robustness in Sticker Retrieval via Cross-Modal Intent Alignment

FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models

How Users Interact with Generative Information Retrieval Systems: A Study of User Behavior and Search Experience

Towards Better Evaluating Multi-Query Sessions: A Measure Based on the Theory of Planned Behavior

Structure-Aware Conversational Legal Case Retrieval

Investigating Conversational Agent Action in Legal Case Retrieval

Constructing Better Evaluation Metrics by Incorporating the Anchoring Effect into the User Model

An Attribute-Driven Mirror Graph Network for Session-based Recommendation

Query Generation and Buffer Mechanism: Towards a better conversational agent for legal case retrieval

Incorporating Query Reformulating Behavior into Web Search Evaluation

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation

GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights

Improving Data Efficiency for Recommenders and LLMs

Off-Policy Evaluation for Large Action Spaces via Policy Convolution

Infinite Recommendation Networks: A Data-Centric Approach

On Sampling Collaborative Filtering Datasets

ECLARE: Extreme Classification with Label Graph Correlations

Off-policy Bandits with Deficient Support

How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements

Sequential Variational Autoencoders for Collaborative Filtering

Rethinking User Retention Modeling in Recommendation

Erratum: Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

ID-centric Pre-training for Recommendation

Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

Curriculum-scheduled knowledge distillation from multiple pre-trained teachers for multi-domain sequential recommendation

Plug-In Diffusion Model for Sequential Recommendation

Style Controlling in Recommendation

DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback

Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback

AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems

Sparse Attention Across Multiple-Context KV Cache

Test-time Prompt Intervention

Breaking the Trade-Off Between Faithfulness and Expressiveness for Large Language Models

Outcome-Grounded Advantage Reshaping for Fine-Grained Credit Assignment in Mathematical Reasoning

Multimodal Hypothetical Summary for Retrieval-based Multi-image Question Answering

LEAP: An LLM-Based Evidence Augmented Pipeline for Table-Based Fact Verification

Towards Realistic Generation: A Multi-Task Agent for Imitating Diverse Character Linguistic Styles

S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models

Object Attribute Matters in Visual Question Answering

Multimodal Table Understanding

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning

Compete to Complete: Co-opetition Adversarial Learning for Retrieval-Augmented Generation

Stop Hardening Everything: A Training-Free Neuron-Level Defense for Neural Ranking Models

Is a Busy Search Agent a Good One? Overthinking and Overretrieval at Scale

AdversarialCoT: Single-Document Retrieval Poisoning for LLM Reasoning

Déjà Vu of Strange Stickers! Enhancing Out-of-Distribution Robustness in Sticker Retrieval via Cross-Modal Intent Alignment

Robust Neural Information Retrieval: An Adversarial and Out-of-Distribution Perspective

Attack-in-the-Chain: Bootstrapping Large Language Models for Attacks Against Black-Box Neural Ranking Models

On the Robustness of Generative Information Retrieval Models: An Out-of-Distribution Perspective

On the Scaling of Robustness and Effectiveness in Dense Retrieval

ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking

Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing

Progressive Adaptation of Large Language Models for Multilingual Text Ranking

Towards Text-Image Interleaved Retrieval

Bridging Modalities: Improving Universal Multimodal Retrieval by Multimodal Large Language Models

An End-to-End Model for Photo-Sharing Multi-Modal Dialogue Generation

Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs

SSRB: Direct Natural Language Querying to Massive Heterogeneous Semi-Structured Data

Human-Robot Coordination Control for Sit-to-Stand Assistance in Hemiparetic Patients With Supernumerary Robotic Leg

Chinese Sequence Labeling with Semi-Supervised Boundary-Aware Language Model Pre-training

TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval

Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting

TInR: Exploring Tool-Internalized Reasoning in Large Language Models

Parallel Test-Time Scaling for Latent Reasoning Models

Towards Text-Image Interleaved Retrieval

Personalized Large Language Model Assistant with Evolving Conditional Memory

Interleaved-Modal Chain-of-Thought

TokenSkip: Controllable Chain-of-Thought Compression in LLMs

Efficient Inference for Large Language Model-based Generative Recommendation

PRInTS: Reward Modeling for Long-Horizon Information Seeking

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs

Multi-Attribute Steering of Language Models via Targeted Intervention

MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning

System 1.x: Learning to Balance Fast and Slow Planning with Language Models

Self-Consistency Preference Optimization

AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge

LASeR: Learning to Adaptively Select Reward Models with Multi-Arm Bandits

Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models

ReGAL: Refactoring Programs to Discover Generalizable Abstractions

Reproducing Adaptive Reranking for Reasoning-Intensive IR

Challenger-Based Combinatorial Bandits for Subcarrier Selection in Ofdm Systems

The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval

Explainable Information Retrieval

FlashCheck: Exploration of Efficient Evidence Retrieval for Fast Fact-Checking

Sample Efficient Demonstration Selection for In-Context Learning

SUNAR: Semantic Uncertainty based Neighborhood Aware Retrieval for Complex QA

ir_explain: A Python Library of Explainable IR Methods

Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets

LiveFC: A System for Live Fact-Checking of Audio Streams

Interpretable knowledge tracing via explicit-implicit alignment

Benchmarking Multimodal Large Language Models for missing modality completion in product catalogues

Bridging NIP and MLM: A Unified Meta-Learning Framework for Sequential Recommendation

Uncertainty-aware Knowledge Tracing

A Content-Driven Micro-Video Recommendation Dataset at Scale

AMBER: Adaptive Meta Balanced Paradigm for Heterogeneous Graph-Based Knowledge Tracing

Frequency-Decoupled Distillation for Efficient Multimodal Recommendation

Video-Bench: Human-Aligned Video Generation Benchmark

ContrastiveGaussian: High-Fidelity 3D Generation with Contrastive Learning and Gaussian Splatting

Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration

Inductive Generative Recommendation via Retrieval-based Speculation

Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Evaluating Language Model Pluralism through In-the-wild Crowd Discussions

SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes

CachePrune: Teaching LLMs What Not to Follow via KV-Cache Editing

Hierarchical Graph-Language Models for Sequential Sentence Classification

Federated Large Language Models: Current Progress and Future Directions

ZoRRO: A Zero-Weight Personalized Recommender System for Scalable News Recommendation

CSyMR: Benchmarking Compositional Music Information Retrieval in Symbolic Music Reasoning

Dual Conditional Diffusion for Sequential Recommendation

RetroLM: Retrieval-Augmented KVs for Long-Context Processing

Boosting Long-Context Information Seeking via Query-Guided Activation Refilling

Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding

Search-o1: Agentic Search-Enhanced Large Reasoning Models

Long Context Compression with Activation Beacon

Tackling the Length Barrier: Dynamic Context Browsing for Knowledge-Intensive Task

MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation

From Matching to Generation: A Survey on Generative Information Retrieval

INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning

A Multi-Task Embedder For Retrieval Augmented LLMs

Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers

C-SEO Bench: Does Conversational SEO Work?

Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs

MetaQA: Combining Expert Agents for Multi-Skill Question Answering

Emotion and Intention Guided Multi-Modal Learning for Sticker Response Selection

RoSA: Enhancing Parameter-Efficient Fine-Tuning via RoPE-aware Selective Adaptation in Large Language Models

Renormalization Group Guided Tensor Network Structure Search

Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval

GeoArena: Evaluating Open-World Geographic Reasoning in Large Vision-Language Models

MTA: A Merge-then-Adapt Framework for Personalized Large Language Models

Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Exploring Recommender System Evaluation: A Multi-Modal LLM Agent Framework for A/B Testing

Bridging Personalization and AI: From RAG to Agent

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation

AdaO2B: Adaptive Online to Batch Conversion for Out-of-Distribution Generalization

Length-Induced Embedding Collapse in PLM-based Models

Media Source Matters More Than Content: Unveiling Political Bias in LLM-Generated Citations

From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions

Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents

Revisiting Clustering of Neural Bandits: Selective Reinitialization for Mitigating Loss of Plasticity

GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents

Fairness-Aware Design for Contextual Experiments: Guaranteeing Reliability and Equity in Heterogeneous Subgroups

ZIPBid: Hierarchical Zero-shot Incremental Spend Planning for Auto-bidding

R&F-Inventory: A Large-Scale Dataset for Monotonic Inventory Estimation in Reach and Frequency Advertising

Expert-Guided Diffusion Planner for Auto-Bidding

Learning Monotonic Probabilities with a Generative Cost Model

S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain

Tutorial: Data Denoising Metrics in Recommender Systems

CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction

Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning

Retrieval-Augmented Generation for AI-Generated Content: A Survey

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs

Incremental Learning for LLM-based Tokenization and Recommendation

Scaling Mesh Generation via Compressive Tokenization

RomanTex: Decoupling 3D-Aware Rotary Positional Embedded Multi-Attention Network for Texture Synthesis

MaterialMVP: Illumination-Invariant Material Generation via Multi-View PBR Diffusion

Unleashing Vecset Diffusion Model for Fast Shape Generation

Long-Sequence Recommendation Models Need Decoupled Embeddings

Scaling Laws for Floating-Point Quantization Training

ChartEditor: A Reinforcement Learning Framework for Robust Chart Editing

Exploring Attention Attractors in Large Language Models

POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering

Movie101v2: Improved Movie Narration Benchmark

VideoOrion: Tokenizing Object Dynamics in Videos

Unified Multimodal Understanding via Byte-Pair Visual Encoding

ChartM3: Benchmarking Chart Editing with Multimodal Instructions

OpenMMEgo: Enhancing Egocentric Understanding for LMMs with Open Weights and Data

Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding

Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective

Interest-Aware Graph Contrastive Learning for Recommendation With Diffusion-Based Augmentation

Generating Difficulty-aware Negative Samples via Conditional Diffusion for Multi-modal Recommendation

Dual-Adaptive Update Strategies-Enhanced Meta-Optimization for User Cold-Start Recommendation

Review-Enhanced Hierarchical Contrastive Learning for Recommendation

Intent-Aware Cross Attention for Next POI Recommendation

MADM: A Model-agnostic Denoising Module for Graph-based Social Recommendation

Contrastive Self-supervised Learning in Recommender Systems: A Survey

Multi-Interest Aware Graph Convolution Network for Social Recommendation

Calibrating Popularity Bias Based on Quality for Recommendation Fairness

Task-Difficulty-Aware Meta-Learning with Adaptive Update Strategies for User Cold-Start Recommendation

CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models

LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases

CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge

Bayesian Inference with Complex Knowledge Graph Evidence

Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering

Verifiable, Debuggable, and Repairable Commonsense Logical Reasoning via LLM-based Theory Resolution

Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation

Self-supervised Contrastive BERT Fine-tuning for Fusion-Based Reviewed-Item Retrieval

LogicRec: Recommendation with Users' Logical Requirements

Bayesian Knowledge-driven Critiquing with Indirect Evidence

GROKE: Vision-Free Navigation Instruction Evaluation via Graph Reasoning on OpenStreetMap

From Single to Multi-agent Reasoning: Advancing GeneGPT for Genomics QA

Benchmarking Large Language Models for Knowledge Graph Validation

Doctron: A Web-based Collaborative Annotation Tool for Ground Truth Creation in IR

Fact Verification in Knowledge Graphs Using LLMs

Grow-on-Demand: Sparse and Adaptive Expert Expansion for Continual Instruction Tuning

Beyond Timestamps: Bridging Forward and Backward Reasoning in Temporal Numerical and Relational Understanding

Hyperbolic Multimodal Generative Representation Learning for Generalized Zero-Shot Multimodal Information Extraction

SMIR: Span-based multi-grained information refinement for joint multimodal entity-relation extraction

Few-shot temporal knowledge graph completion based on query-adaptive Mamba-enhanced temporal relation learning

Bring Invariant to Variant: A Contrastive Prompt-based Framework for Temporal Knowledge Graph Forecasting

TimeR⁴ : Time-aware Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answering

Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph Completion

DuoKD: Dual Knowledge Distillation from Large Language Models for Robust Graph Neural Networks

Mitigating Noise and Imbalance in Social Governance Graphs for Multi-Type Risk Assessment

MUG: Meta-path-aware Universal Heterogeneous Graph Pre-Training

Structure-Enhanced Adapter for Self-Supervised Heterogeneous Graph Learning

KG-BiLM: Knowledge Graph Embedding via Bidirectional Language Models

Unveiling Backdoor Propagation in Graphs: Neuron-Centric Defense Mechanisms

LEDA: Latent Semantic Distribution Alignment for Multi-domain Graph Pre-training

Topology-Aware Feature Sorting Enables Universal Modeling on Homophilic and Heterophilic Graphs

Integrated Mixture of Neighborhood and Community Experts for Graph-Based Fraud Detection

Towards Graph Foundation Model: Node Feature Transfer Invariant Modeling on General Graphs

SGSST: Scaling Gaussian Splatting Style Transfer

Flow Matching for Collaborative Filtering

Balancing Fine-tuning and RAG: A Hybrid Strategy for Dynamic LLM Recommendation Updates

Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation

Federated Conversational Recommender Systems

Countering Mainstream Bias via End-to-End Adaptive Local Learning

LLMs for User Interest Exploration in Large-scale Recommendation Systems

Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs

Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification

Closed-book Question Generation via Contrastive Learning

LiR3AG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation

AuditAgent: LLM Agent for Risks Auditing in Recommender Systems

BaseCal: Unsupervised Confidence Calibration via Base Model Signals

The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics Analysis

Multi-Behavior Sequential Modeling with Transition-Aware Graph Attention Network for E-Commerce Recommendation

Interaction-level Membership Inference Attack for Recommender Systems via Cluster-based User Modeling

InductionBench: LLMs Fail in the Simplest Complexity Class

The Mirage of Model Editing: Revisiting Evaluation in the Wild

Jailbreak LLMs through Internal Stance Manipulation

Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs

FashionMAC: Deformation-Free Fashion Image Generation with Fine-Grained Model Appearance Customization

Learning from multi-view fragments: An adaptive consistency distillation framework for occluded person re-identification

PRVR: Partially Relevant Video Retrieval

Mitigating Multilingual Hallucination in Large Vision-Language Models

Dynamic Adapter with Semantics Disentangling for Cross-lingual Cross-modal Retrieval

Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network

Towards Ship License Plate Recognition in the Wild: A Large Benchmark and Strong Baseline

Cooperative or Competitive? Understanding the Interaction between Attention Heads From A Game Theory Perspective

Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning

Multimodal Language Models See Better When They Look Shallower

CHOIR: Harmonizing Structured Persona Diversity for Robust Collaborative LLM Reasoning

DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management

Language Models as Semantic Augmenters for Sequential Recommenders

Personalization in the Era of Super(?)-intelligence

Third Workshop on Generative AI for Recommender Systems and Personalization

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation

GraphCheck: Breaking Long-Term Text Barriers with Extracted Knowledge Graph-Powered Fact-Checking

Masculine Defaults via Gendered Discourse in Podcasts and Large Language Models

I want a horror - comedy - movie: Slips-of-the-Tongue Impact Conversational Recommender System Performance

Flow Matching for Collaborative Filtering

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding

How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality

Beyond Relevance: Utility-Centric Retrieval in the LLM Era

How Do LLM-Generated Texts Impact Term-Based Retrieval Models?

Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception

Bridging Queries and Tables through Entities in Open-Domain Table Retrieval

Tailoring Table Retrieval from a Field-aware Hybrid Matching Perspective

Utility-Focused LLM Annotation for Retrieval and Retrieval-Augmented Generation

CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification

GSM-EL: A Generalizable Symbol-Manipulation Approach for Entity Linking

Boosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings

LLM-Aligned Geographic Item Tokenization for Local-Life Recommendation

FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion

OneRec-Think: In-Text Reasoning for Generative Recommendation

CE-GPPO: Coordinating Entropy via Gradient-Preserving Clipping Policy Optimization in Reinforcement Learning

PushGen: Push Notifications Generation with LLM

ChorusCVR: Chorus Supervision for Entire Space Post-Click Conversion Rate Modeling

OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service

Toward Generalized Web Agent Training: A Deep Dive into Entropy-Balanced Reinforcement Learning

Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce

Inference Scaling Law for Retrieval Augmented Generation

The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG

Latent Retrieval Augmented Generation

Calibrating Uncertainty with Cross-Model Consistency for LLM Hallucination Mitigation

SCORE-RAG: Self-Correcting Exploration-Exploitation Retrieval for Multi-hop Question Answering

Why Knowledge Distillation Fails to Scale in Neural Retrieval

Cascaded Verification Framework: A Progressive Approach for Mitigating Hallucinations in Large Language Models

Activation Caching for Retrieval-Augmented Generation

DynKGRAG: A framework for dynamic knowledge graph construction and multi-hop querying over numerical and textual data

When MLLMs Meet ICH: A visual retrieval-augmented generation-based method for intangible cultural heritage image recognition-take Shadow Puppetry as a case

Adaptive Continual Learning with User-Incremental Forward Compatibility for Meta-Augmented Cold-Start Recommenders

MESA: Plugin Meta-Modulation for Transformer-Based Cold-Start Sequential Recommendation

Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery

Multi-Agent Deep Reinforcement Learning With Trajectory Prediction for Task Migration-Assisted Computation Offloading

Dual-Adaptive Update Strategies-Enhanced Meta-Optimization for User Cold-Start Recommendation

Review-Enhanced Hierarchical Contrastive Learning for Recommendation

Guiding Graph Learning with Denoised Modality for Multi-modal Recommendation

Multi-agent reinforcement learning for vehicular task offloading with multi-step trajectory prediction

Graph Diffusion-Based Representation Learning for Sequential Recommendation

Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation

Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables

Adversarial Contrastive Learning for Evidence-Aware Fake News Detection With Graph Neural Networks

Counterfactual Debiasing for Fact Verification

Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention

Evidence-aware Fake News Detection with Graph Neural Networks

Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval

BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation

Reinforced Informativeness Optimization for Long-Form Retrieval-Augmented Generation

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation

Unveiling Knowledge Utilization Mechanisms in LLM-based Retrieval-Augmented Generation

Self-Calibrated Listwise Reranking with Large Language Models

REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering

Dense Text Retrieval Based on Pretrained Language Models: A Survey

TOME: A Two-stage Approach for Model-based Retrieval

Less Learn Shortcut: Analyzing and Mitigating Learning of Spurious Feature-Label Correlation

DuReader-Retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine

Nested Browser-Use Learning for Agentic Information Seeking

Causal Prompting: Debiasing Large Language Model Prompting Based on Front-Door Adjustment

SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation

WebWalker: Benchmarking LLMs in Web Traversal

PROPER: A Progressive Learning Framework for Personalized Large Language Models with Group-Level Adaptation

AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment

SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding

AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptation

OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking

EvolveSearch: An Iterative Self-Evolving Search Agent

Imagine with Layout and Sketch: Enhancing Vision-Language Retrieval with Dual-Stream Multi-Modal Query Refinement

Suit the Remedy to the Retriever: Interpretable Query Optimization with Retriever Preference Alignment for Vision-Language Retrieval

Heterogeneous Uncertainty-Guided Composed Image Retrieval with Fine-Grained Probabilistic Learning

Towards Efficient Low-rate Image Compression with Frequency-aware Diffusion Prior Refinement

HALoRA: Low-Rank Adaptation with Hierarchical Budget Allocation for Efficient Vision-Language Alignment

From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents

FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction

Efficient Self-Supervised Video Hashing with Selective State Spaces

EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models

Modeling Uncertainty in Composed Image Retrieval via Probabilistic Embeddings

Evaluation Validity in Information Retrieval

On the Use of LLMs for Relevance Labelling

LLM4Eval: Large Language Model for Evaluation in IR

System Comparison Using Automated Generation of Relevance Judgements in Multiple Languages

LLM4Eval@WSDM 2025: Large Language Model for Evaluation in Information Retrieval

Enhancing Human Annotation: Leveraging Large Language Models and Efficient Batch Processing

What Matters in a Measure? A Perspective from Large-Scale Search Evaluation

Large Language Models can Accurately Predict Searcher Preferences

LLM4Eval: Large Language Model for Evaluation in IR

Taking Search to Task

Off-Policy Learning with Limited Supply

Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits

POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition

A General Framework for Off-Policy Learning with Partially-Observed Reward

Off-Policy Evaluation and Learning for the Future under Non-Stationarity

MultiScale Contextual Bandits for Long Term Objectives

Off-Policy Evaluation and Learning for Matching Markets

An Off-Policy Learning Approach for Steering Sentence Generation towards Personalization

CONSEQUENCES 2025 - The 4th Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems

Multiple Function Merging for Code Size Reduction

The Effects of Thinking Aloud on Participants during Search and Sensemaking

Workshop on Generative AI and Academic Search (GAI&AS)

The effects of goal-setting on learning during information seeking with generative AI

A Questionnaire for Capturing Perceptions of Self-Regulated Learning Processes during Information Seeking

Multilingual and Domain-Agnostic Tip-of-the-Tongue Query Generation for Simulated Evaluation

The Effects of Working Memory during a Search and Sensemaking Task

Search+Chat: Integrating Search and GenAI to Support Users with Learning-oriented Search Tasks

Tip of the Tongue Query Elicitation for Simulated Evaluation

The Effects of Goal-setting on Learning Outcomes and Self-Regulated Learning Processes

Better Understanding Procedural Search Tasks: Perceptions, Behaviors, and Challenges

Beyond Unimodal Perspectives: Generative Retrieval with Multimodal Semantics

LinkGPT: Leveraging Large Language Models for Enhanced Link Prediction in Text-Attributed Graphs

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning

On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks

TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning

Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices

CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment

Touch and Go: Learning from Human-Collected Vision and Touch

NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases

Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding

BracketRank: Large Language Model Document Ranking via Reasoning-based Competitive Elimination

Question Difficulty Estimation for Large Language Models via Answer Plausibility Scoring

It's High Time: A Survey of Temporal Question Answering

The 9th International Workshop on Narrative Extraction from Text: Text2Story 2026

One Model, Many Guidelines: Instruction Fine-Tuning for Historical Named Entity Recognition

Reference-free Evaluation at Inference for NER/NEL over OCRed Historical Texts

Are LLM-Based Retrievers Worth Their Cost? An Empirical Study of Efficiency, Robustness, and Reasoning Overhead

Beyond Maintenance: A Benchmark and Multi-Agent Framework for Repository-Usage Code Generation

Context Convergence Improves Answering Inferential Questions

Pretraining Exposure Explains Popularity Judgments in Large Language Models

Renormalization Group Guided Tensor Network Structure Search

MTA: A Merge-then-Adapt Framework for Personalized Large Language Models

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Exploring Recommender System Evaluation: A Multi-Modal LLM Agent Framework for A/B Testing

Rethinking Semantic-Collaborative Integration: Why Alignment Is Not Enough

GRAND: A Robust Diffusion Framework for Multi-Granularity Graph Anomaly Detection in Web Platforms

SAGE: Global Semantic Alignment with LLMs for Long-Tail Sequential Recommendation

ARCHER: Shooting Straight in Multimodal E-Commerce Search at Alibaba with Progressive Alignment

NEZHA: A Zero-sacrifice and Hyperspeed Decoding Architecture for Generative Recommendations

To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention

From Doxa to Logos in Scientific Peer Review

Peerispect: Claim Verification in Scientific Peer Reviews

PeerPrism: Peer Evaluation Expertise vs Review-writing AI

Can LLMs Uphold Research Integrity? Evaluating the Role of LLMs in Peer Review Quality

Diffusion-based generative modeling for expert team formation

Query Performance Prediction Using Neural Query Space Proximity

Building Trustworthy Peer Review Quality Assessment Systems

ProActLLM: Proactive Conversational Information Seeking with Large Language Models

RottenReviews: Benchmarking Review Quality with Human and LLM-Based Judgments

exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem

How to Improve LLMs' Performance on Specific Languages: A Perspective on LLM-Derived Language Similarity

Attention as Selector: Unlocking VLM Attention for Long Document Page Retrieval

GAS: Geometry-Appearance Synergy for Consistent Video Customization

Audio-Guided Video Scene Editing

Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback

Scalable Vision-Language Understanding and Generation

MuTIS: Enhancing Reasoning Efficiency through Multi Turn Intervention Sampling in Reinforcement Learning

H3R: Hybrid Multi-view Correspondence for Generalizable 3D Reconstruction

HUST: High-Fidelity Unbiased Skin Tone Estimation via Texture Quantization

From Trial to Triumph: Advancing Long Video Understanding via Visual Context Sample Scaling and Self-Reward Alignment

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning

Compete to Complete: Co-opetition Adversarial Learning for Retrieval-Augmented Generation

Stop Hardening Everything: A Training-Free Neuron-Level Defense for Neural Ranking Models

Generative Store Retrieval in Taobao Search

Is a Busy Search Agent a Good One? Overthinking and Overretrieval at Scale

AdversarialCoT: Single-Document Retrieval Poisoning for LLM Reasoning

One-Pass Decoding for Generative Recommendation with WFST-Constrained A* Search

Déjà Vu of Strange Stickers! Enhancing Out-of-Distribution Robustness in Sticker Retrieval via Cross-Modal Intent Alignment

LongRanker: Efficient One-Pass Document Reranking with Long-Context Large Language Models

CorpusBrain++: A Continual Generative Pre-Training Framework for Knowledge-Intensive Language Tasks

ShoppingBench: A Real-World Intent-Grounded Shopping Benchmark for LLM-based Agents

REG4Rec: Reasoning-Enhanced Generative Model for Large-Scale Recommendation Systems

RCLRec: Reverse Curriculum Learning for Modeling Sparse Conversions in Generative Recommendation

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation

Thinking Broad, Acting Fast: Latent Reasoning Distillation from Multi-Perspective Chain-of-Thought for E-Commerce Relevance

Infer As You Train: A Symmetric Paradigm of Masked Generative for Click-Through Rate Prediction

Oblique-MERF: Revisiting and Improving MERF for Oblique Photography

Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation

Resource Trading for Vehicular Edge Computing Networks: A Trust-Based Double Auction Approach

D2MoRA: Diversity-Regulated Asymmetric MoE-LoRA Decomposition for Efficient Multi-Task Adaptation

COMBINER: Composed Image Retrieval Guided by Attribute-Based Neighbor Relations

A Comprehensive Survey on Composed Image Retrieval

ENCODER: Entity Mining and Modification Relation Binding for Composed Image Retrieval

Pseudo Triplet Guided Few-shot Composed Image Retrieval

HUD: Hierarchical Uncertainty-Aware Disambiguation Network for Composed Video Retrieval

Multi-modal Recommendation with Joint Content and Interaction Augmentation

Spatial Understanding from Videos: Structured Prompts Meet Simulation Data

FiRE: Enhancing MLLMs with Fine-Grained Context Learning for Complex Image Retrieval

Interactive Garment Recommendation with User in the Loop

Matryoshka Representation Learning for Recommendation with Layer- and Hardness-Adaptive Negative Sampling

DAR: Dimension-Adaptive Recommendation with Multi-Granular Noise Control

Proxy-enhanced cross-domain sequential recommendation

Denoising and Augmented Negative Sampling for Collaborative Filtering

Adaptive Hardness Negative Sampling for Collaborative Filtering

Proxy-Aware Cross-Domain Sequential Recommendation

Augmented Negative Sampling for Collaborative Filtering

Disentangled Negative Sampling for Collaborative Filtering

Multi-Faceted Global Item Relation Learning for Session-Based Recommendation

WISE: Word-Level Interaction-Based Multimodal Fusion for Speech Emotion Recognition

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

Room Matters: Dynamic Room-level Collaboration Information Modeling for Live Streaming Recommendation

Disentangled Interest Network for Out-of-Distribution CTR Prediction

Pantheon: Personalized Multi-objective Ensemble Sort via Iterative Pareto Policy Optimization

Solar Forecasting with Causality: A Graph-Transformer Approach to Spatiotemporal Dependencies

RecFlow: An Industrial Full Flow Recommendation Dataset

Bridging Short Videos and Streamers with Multi-Graph Contrastive Learning for Live Streaming Recommendation

Solar Multimodal Transformer: Intraday Solar Irradiance Predictor Using Public Cameras and Time Series

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

UniSAR: Modeling User Transition Behaviors between Search and Recommendation

Shedding the Facades, Connecting the Domains: Detecting Shifting Multimodal Hate Video with Test-Time Adaptation

ACE-HVD: A Multi-Agent Collaboration Approach for Interpretable Hate Video Detection

TAMEing Long Contexts in Personalization: Towards Training-Free and State-Aware MLLM Personalized Assistant

From Shallow Humor to Metaphor: Towards Label-Free Harmful Meme Detection via LMM Agent Self-Improvement

Nip Rumors in the Bud: Retrieval-Guided Topic-Level Adaptation for Test-Time Fake News Video Detection

COMMANDing anomalies: Continual video anomaly detection via dual-memory and temporal mamba modeling

Enhancing fake news video detection with self-driven question-answer from LMMs

MATCH: Multi-Agentic Evidence Grounding for Explainable Hate Video Detection

In-context Prompt-augmented Micro-video Popularity Prediction

Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning

GAM: A Generative Auto-Marketing Framework in Online E-commerce Platforms

Automated Deterministic Auction Design with Objective Decomposition

DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs

Marketing Hosting: From Fixed to Endogenous Budgets

Beyond Advertising: Mechanism Design for Platform-Wide Marketing Service "QuanZhanTui"

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lens

Learning against Non-credible Second-Price Auctions

Generative Auto-bidding via Conditional Diffusion Modeling

AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games

Mm-Embed: Universal Multimodal Retrieval with Multimodal LLMS

Unifying Multimodal Retrieval via Document Screenshot Embedding

FLAME : Factuality-Aware Alignment for Large Language Models

CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval

mAggretriever: A Simple yet Effective Approach to Zero-Shot Multilingual Dense Retrieval

Improving Conversational Passage Re-ranking with View Ensemble

SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted Indexes

One Blade for One Purpose: Advancing Math Information Retrieval using Hybrid Search

Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage Retrieval

A Dense Representation Framework for Lexical and Semantic Matching

Multi-Modal Correction Network for Recommendation

Temporal Uplift Modeling for Online Marketing

Deep Session Heterogeneity-Aware Network for Click Through Rate Prediction

Graph-aware collaborative reasoning for click-through rate prediction

Deep Dynamic Interest Learning With Session Local and Global Consistency for Click-Through Rate Predictions

Attention Basin: Why Contextual Position Matters in Large Language Models

Compress to One Point: Neural Collapse for Pre-Trained Model-Based Class-Incremental Learning

Intent-driven In-context Learning for Few-shot Dialogue State Tracking

MindGYM: What Matters in Question Synthesis for Thinking-Centric Fine-Tuning?

Robust Temporal Action Localization With Meta Boundary Refinement

Exploiting Intrinsic Multilateral Logical Rules for Weakly Supervised Natural Language Video Localization

Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation

Class-Incremental Unsupervised Domain Adaptation via Pseudo-Label Distillation

Bilateral Relation Distillation for Weakly Supervised Temporal Action Localization

Point-Supervised Video Temporal Grounding

Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMs

Localizing Factual Inconsistencies in Attributable Text Generation

MDCure: A Scalable Pipeline for Multi-Document Instruction-Following

MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs

Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision

Bridging the Visual Gap: Fine-Tuning Multimodal Models with Knowledge-Adapted Captions

3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model

Contrastive Sequential-Diffusion Learning: Non-Linear and Multi-Scene Instructional Video Synthesis

Synergistic Effects of Fascia Knife and TCM on Hamstring Fatigue Recovery in Track Athletes: An Electromyographic Evaluation

Hierarchical Semantics Interaction for Compressed Video Action Recognition

Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection

Cross-domain Rumor Detection via Test-Time Adaptation and Large Language Models

VCSA: Video Copy Localization Via Single Frame Annotation

EarlyMix: Hierarchical Mixing for Early Time Series Classification

UTSC: Uncertainty-Aware Framework for Early Time Series Classification

Event Consistency-aware Robust Fake News Detection

Evaluating and Mitigating Sycophancy in Large Vision-Language Models

Fine-tuning Bias Neurons for Fair Text-to-Image Generation

Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning

MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding

Mutual-Taught for Co-adapting Policy and Reward Models

Small LLMs Are Weak Tool Learners: A Multi-LLM Agent

Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration

Multi-Party Conversation Modeling for Emotion Recognition

Multi-Grained Knowledge Retrieval for End-to-End Task-Oriented Dialog

Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System

Generic Dependency Modeling for Multi-Party Conversation

DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition

INTENT: Invariance and Discrimination-aware Noise Mitigation for Robust Composed Image Retrieval

HABIT: Chrono-Synergia Robust Progressive Learning Framework for Composed Image Retrieval

Multi-modal Bipartite Graph Structure Learning with Information Bottleneck for Micro-video Recommendation

MRG-Mamba: A novel multi-rate cross-condition model for industrial remaining useful life prediction

Introduction to the Special Issue on Multimodal Video Understanding and Analysis with Foundation Models

Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation

Fine-tuning Multimodal Large Language Models for Product Bundling

DCount: Decoupled Spatial Perception and Attribute Discrimination for Referring Expression Counting

Mitigating Hallucination Through Theory-Consistent Symmetric Multimodal Preference Optimization

PromptDSI: Prompt-Based Rehearsal-Free Continual Learning for Document Retrieval

From SERPs to Agents: A Platform for Comparative Studies of Information Interaction

In-Browser Agents for Search Assistance

Simulation of Interactive Information Retrieval: A Guided Tour

The Third Search Futures Workshop at ECIR'26

The Third International Workshop on Open Web Search (WOWS)

Creating Specialized RAG-Based Search Engines Using the Open Web Index

Beyond the Click: A Framework for Inferring Cognitive Traces in Search

SimEval-IR: A Unified Toolkit and Benchmark Suite for Evaluating User Simulators and Search Sessions

AgentSim: A Platform for Verifiable Agent-Trace Simulation

IIRSim Studio: A Dashboard for User Simulation

Disentangled Object-Centric Image Representation for Robotic Manipulation

Distributional Reinforcement Learning with Dual Expectile-Quantile Regression

Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset

SARDINE: Simulator for Automated Recommendation in Dynamic and Interactive Environments

An Offline Metric for the Debiasedness of Click Models

Generative Slate Recommendation with Reinforcement Learning

Evaluating the Robustness of Click Models to Policy Distributional Shift

Reinforced Efficient Reasoning via Semantically Diverse Exploration

MCoT-MVS: Multi-level Vision Selection by Multi-modal Chain-of-Thought Reasoning for Composed Image Retrieval

R2NS: Recall and Re-ranking of Negative Samples for Sequential Recommendation

Beyond efficient fine-tuning: Efficient hybrid fine-tuning of CLIP models guided by explainable ViT attention

OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs

Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning

Offline Trajectory Optimization for Offline Reinforcement Learning

How Does Topology Bias Distort Message Passing in Graph Recommender? A Dirichlet Energy Perspective

Measuring Interaction-Level Unlearning Difficulty for Collaborative Filtering

AgentIR: 2nd Workshop on Agent-based Information Retrieval

History-Aware Reasoning for GUI Agents

ProBench: Benchmarking GUI Agents with Accurate Process Information

RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning Models

EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering

Efficient Memory Alignment for Long-term Conversational Information Seeking

Code-Based English Models Reveal Surprising Performance on Chinese QA Pair Extraction Task

Issue Localization via LLM-Driven Iterative Code Graph Searching

PEACE: Towards Efficient Project-Level Efficiency Optimization via Hybrid Code Editing

PG-Agent: An Agent Powered by Page Graph

Towards an Inclusive Mobile Web: A Dataset and Framework for Focusability in UI Accessibility

Cross-modal Prompting for Balanced Incomplete Multi-modal Emotion Recognition

Bolster Hallucination Detection via Prompt-Guided Data Augmentation

Dual-Attention Video Representation Learning for Parameter Efficient Text-Video Retrieval

LEGEND: Leveraging Representation Engineering to Annotate Safety Margin for Preference Datasets

OT-StainNet: Optimal Transport Driven Semantic Matching for Weakly Paired H&E-to-IHC Stain Transfer

Transferable Adversarial Face Attack with Text Controlled Attribute

Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models

Correlated Multiple IHC Virtual Staining for Breast Histopathological Images

PolaFormer: Polarity-aware Linear Attention for Vision Transformers

Synthesizing Spreading-out features for generative zero-shot image classification

Rethinking Video-Language Model from the Language Input Perspective

Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models

Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning Models

Generating transferable attacks across large vision-language models using adversarial deformation learning

Are Large Vision-Language Models Robust to Adversarial Visual Transformations?

Mitigating Multilingual Hallucination in Large Vision-Language Models

Cooperative or Competitive? Understanding the Interaction between Attention Heads From A Game Theory Perspective

PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models

Multi-level Association Refinement Network for Dialogue Aspect-based Sentiment Quadruple Analysis

Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning

EvoNarrator: Modeling Scientific Evolution for Feasible Hypothesis Generation

DART: Empowering LLM-Based Agents on Domain-Specific Tasks through Dynamic Augmented Reasoning Trees

Diagnosing LLM Benchmark: A Psychometric Analysis of Difficulty and Discrimination

Uncertainty-penalized reinforcement learning from human feedback with diversified reward LoRA ensembles

Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models

Correcting Large Language Model Behavior via Influence Function

GRACE: Graph-Adapted Case-Augmented Execution for Tool Use in Large Language Models

Extracting Reasoning Patterns from Knowledge Graph to Enhance LLMs' Reasoning Capability

Preference-Strength-Aware Self-Improving Alignment with Generative Preference Models

Empowering Large Language Model Agent through Step-Level Self-Critique and Self-Training

Retrieval is NOT always needed: Exploring the timing of retrieval in dynamic retrieval-augmented generation

WikiREVIEW: A Multi-Perspective Review Framework for Automatic Wiki-Style Article Generation

Your Reasoning Model Knows What Counts: Self-Guided Chain-of-Thought Pruning for Efficient Reasoning

G-CoS: An Interpretable Gain-Cost Framework for User Satisfaction Estimation in Generative Information Retrieval

A Fact-Checking Framework with Denoising Evidence Retrieval and LLM-Based Debate Verification

Dual-Debias: A counterfactual inference framework for causally robust fact-checking

BLADE: Enhancing Black-Box Large Language Models with Small Domain-Specific Models

SimVBG: Simulating Individual Values by Backstory Generation

CompKBQA: Component-wise Task Decomposition for Knowledge Base Question Answering

Detecting Hallucination in Large Language Models Through Deep Internal Representation Analysis

SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data Science

Automated Visualization Code Synthesis via Multi-path Reasoning and Feedback-Driven Optimizations

A New Query Expansion Approach for Enhancing Information Retrieval via Agent-Mediated Dialogic Inquiry

Question-to-Knowledge (Q2K): Multi-Agent Generation of Inspectable Facts for Product Mapping

Learning to Reason from Feedback at Test-Time

Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene Understanding

Fine-Grained Spatiotemporal Grounding on Egocentric Videos

AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning

Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors

A Mutual Supervision Framework for Referring Expression Segmentation and Generation

Making Long-Context Language Models Better Multi-Hop Reasoners

Towards Learning a Generalist Model for Embodied Navigation

Beyond Embeddings: The Promise of Visual Table in Visual Reasoning

MVP-Tuning: Multi-View Knowledge Retrieval with Prompt Tuning for Commonsense Reasoning

CPG: Contrastive Patch-Graph learning for 3D point cloud

MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval

Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information Retrieval

MLVU: Benchmarking Multi-task Long Video Understanding

Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding

OmniGen: Unified Image Generation

MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval

VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval

FAT: Field-Aware Transformer for Point Cloud Segmentation With Adaptive Attention Fields

Fat: Field-Aware Transformer for 3D Point Cloud Semantic Segmentation

Counterfactual Fairness with Imperfect Causal Graphs

MLLM Enriched Explainable Multiple Clustering

AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning

Enhancing Graph Condensation via Key Information Reconstruction

Federated Recommendation via Stochastic Aggregation and Consistency Inference

GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphs

CrystalICL: Enabling In-Context Learning for Crystal Generation

Towards a Unified Framework of Clustering-based Anomaly Detection

Concept-Centric Token Interpretation for Vector-Quantized Generative Models

DimCL: Dimension-Aware Augmentation in Contrastive Learning for Recommendation

Multilingual and Domain-Agnostic Tip-of-the-Tongue Query Generation for Simulated Evaluation

LTRR: Learning To Rank Retrievers for LLMs

Evaluation of Agents under Simulated AI Marketplace Dynamics

AgentSearch: Indexing, Retrieval, and Ranking of AI Agents

Diversification as Risk Minimization

Recall, Robustness, and Lexicographic Evaluation

MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor

The Second Tutorial on Retrieval-Enhanced Machine Learning: Synthesis and Opportunities

Tip of the Tongue Query Elicitation for Simulated Evaluation

S²Drug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening

ConSurv: Multimodal Continual Learning for Survival Analysis

Deep Research with Open-Domain Evaluation and Multi-Stage Guardrails for Safety

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation

FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs

Generative Archetype-Grounded Item Representations for Sequential Recommendation

DP-DGAD: A Generalist Dynamic Graph Anomaly Detector with Dynamic Prototypes

Community-aware multi-granularity contrastive learning for graph anomaly detection

Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling

Speech Watermarking with Discrete Intermediate Representations

CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling

Language-Codec: Bridging Discrete Codec Representations and Speech Language Models

ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control

Rhythm Controllable and Efficient Zero-Shot Voice Conversion via Shortcut Flow Matching

VoxpopuliTTS: a large-scale multilingual TTS corpus for zero-shot speech generation

Mitigating Hallucinations in LM-Based TTS Models via Distribution Alignment Using GFlowNets

Enhancing Expressive Voice Conversion with Discrete Pitch-Conditioned Flow Matching Model

Open-Set Cross Modal Generalization via Multimodal Unified Representation

Satellite-Text-Prompted Large Language Model for Photovoltaic Power Forecasting

SGMT: Social Generating with Multiview-Guided Tuning In Recommender Systems

Diversity Recommendation via Causal Deconfounding of Co-purchase Relations and Counterfactual Exposure

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning

CPGRec+: A Balance-Oriented Framework for Personalized Video Game Recommendations

CoDeR+: Interest-aware Counterfactual Reasoning for Sequential Recommendation

Understanding Over-Squashing in Dynamic Graphs

FashionTailor: Controllable Clothing Editing for Human Images with Appearance Preserving

CoDeR: Counterfactual Demand Reasoning for Sequential Recommendation

RocketEval: Efficient automated LLM evaluation via grading checklist

RetroLM: Retrieval-Augmented KVs for Long-Context Processing

FinSight: Towards Real-World Financial Deep Research

Reinforcing Agentic Search Via Reward Density Optimization

Boosting Long-Context Information Seeking via Query-Guided Activation Refilling

Evolving Graph-Based Context Modeling for Multi-Turn Conversational Retrieval-Augmented Generation

Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimization

Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization

Tackling the Length Barrier: Dynamic Context Browsing for Knowledge-Intensive Task

WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Scent of Knowledge: Optimizing Search-Enhanced Reasoning with Information Foraging

Conversational Learning Diagnosis via Reasoning Multi-Turn Interactive Learning

Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

GraphPrompter: Multi-Stage Adaptive Prompt Optimization for Graph In-Context Learning

Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor

BoxCD: Leveraging Contrastive Probabilistic Box Embedding for Effective and Efficient Learner Modeling

Empowering Federated Graph Rationale Learning with Latent Environments

Learning from shortcut: a shortcut-guided approach for explainable graph learning

Semantic-Aligned Code Summarization: Bridging the Gap Between Code and Natural Language Through Data Flow Analysis

Zero-1-to-3: Domain-Level Zero-Shot Cognitive Diagnosis via One Batch of Early-Bird Students towards Three Diagnostic Objectives

FedJudge: Federated Legal Large Language Model

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs

Optimal Transport Enhanced Cross-City Site Recommendation

OpenSiteRec: An Open Dataset for Site Recommendation

Contrastive Graph Pooling for Explainable Classification of Brain Networks

Corrections to "Contrastive Graph Pooling for Explainable Classification of Brain Networks"

Conditional Cross-Platform User Engagement Prediction

REST: Drug-Drug Interaction Prediction via Reinforced Student-Teacher Curriculum Learning

Towards Automatic ICD Coding via Knowledge Enhanced Multi-Task Learning

IMF: Interactive Multimodal Fusion Model for Link Prediction

Gromov-Wasserstein Guided Representation Learning for Cross-Domain Recommendation

Scaling Human-Centric Trustworthy Foundation Model via Advanced Reasoning and Agentic Frameworks

CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation

Learning Diverse Responses with Prefix-Conditioned Supervised Fine-Tuning

Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning Models

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

MMBoundary: Advancing MLLM Knowledge Boundary Awareness through Reasoning Step Confidence Calibration

VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues

PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent

Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement

Aligning LLMs with Individual Preferences via Interaction

Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

Act as you think: Reinforcing Consistent Reasoning in Medical Visual Question Answering

Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification

SocialStep: Fast Prediction of Social Determinants of Health

Compliance and factuality of large language models for clinical research document generation

Long-Term EEG Partitioning for Seizure Onset Detection

Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations

SECRET: Semi-supervised Clinical Trial Document Similarity Search

RHealth: A R Toolkit for Deep Learning in Healthcare

s3: You Don't Need That Much Data to Train a Search Agent via RL

AdaMCoT: Rethinking Cross-Lingual Factual Reasoning Through Adaptive Multilingual Chain-of-Thought

Programming over Thinking: Efficient and Robust Multi-Constraint Planning

Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment

MMAC: A Multilingual, Multimodal Alignment Framework for Cultural Grounding Evaluation

Leveraging LLMs for Dynamic Engagement Pattern Recognition in Collaborative Learning

Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts

SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series

Structure from rank: Rank-order coding as a bridge from sequence to structure

MEDSAGE: Enhancing Robustness of Medical Dialogue Summarization to ASR Errors with LLM-generated Synthetic Dialogues

What Makes a Good Natural Language Prompt?

Causality-Aligned Semantic Recovery for Incomplete Cross-Modal Retrieval

DeFT-LoRA: Decoupled and Fused Tuning with LoRA Experts for Universal Cross-Domain Retrieval

Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning

Multi-Agent Debate based Concept Augmentation for Enhanced Cognitive Diagnosis

BalDRO: A Distributionally Robust Optimization based Framework for Large Language Model Unlearning

From Social Media to Psychological Scale: An Adaptive Framework with Two-Hop Retrieval for Depression Screening

Towards personalized long-term learning modeling in knowledge tracing

Explicit token modeling and hierarchical feature reasoning for multimodal fake news detection

Gradually Vanishing Gap in Prototypical Network for unsupervised domain adaptation

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models

FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation

Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding

CompactIE: Compact Facts in Open Information Extraction

A Multilingual Multimodal Medical Examination Dataset for Visual Question Answering in Healthcare

SOLVE-Med: Specialized Orchestration for Leading Vertical Experts Across Medical Specialties

SynthMed: Generating and Detecting Multimodal Deepfakes for Healthcare Communication

AMICO: A Semantic and Multimodal Framework for AI-Assisted Clinical Reporting

Combining Evidence and Reasoning for Biomedical Fact-Checking

Combating Biomedical Misinformation through Multi-modal Claim Detection and Evidence-based Verification

HFR-MKGC: Hierarchical Fusion Reasoning with MLLMs for Multi-modal Knowledge Graph Completion

Rethink Representation Learning for Questionnaire Data

ST-VLM: A Spatial-to-Image Multimodal Spatial-Temporal Prediction Framework with Vision-Language Model

Multi-Granularity Multi-Modal Knowledge Graph Representation Learning via Subgraph-Aware Adaptive Fusion and Hierarchical Relation Modeling

Addressing graph heterogeneity and heterophily from a spectral perspective

Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal

Medusa: A Multi-Scale High-order Contrastive Dual-Diffusion Approach for Multi-View Clustering

MFLCP: Personalized Multimodal Federated Learning via Collaborative Prompting with Missing Modalities

Dynamic Self-adaptive Multiscale Distillation from Pre-trained Multimodal Large Model for Efficient Cross-modal Retrieval

Asymmetric Pre-aligned Anchor Contrastive Enhanced Diffusion Hashing Model for Incomplete Multimodal Retrieval

QE-RAG: A Robust Retrieval-Augmented Generation Benchmark for Query Entry Errors

Trigger3: Refining Query Correction via Adaptive Model Selector

ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability

GREAT: Guiding Query Generation with a Trie for Recommending Related Search about Video at Kuaishou

GenSAR: Unifying Balanced Search and Recommendation with Generative Retrieval

Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation

ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding

LargePiG for Hallucination-Free Query Generation: Your Large Language Model is Secretly a Pointer Generator

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Large Language Models Enhanced Collaborative Filtering

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search

LISRec: Modeling User Preferences with Learned Item Shortcuts for Sequential Recommendation

RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards

Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning

Harnessing Webpage UIs for Text-Rich Visual Understanding

Fact-Aware Multimodal Retrieval Augmentation for Accurate Medical Radiology Report Generation

ORBIT - Open Recommendation Benchmark for Reproducible Research with Hidden Tests

ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation

DATE-LM: Benchmarking Data Attribution Evaluation for Large Language Models

Group-Level Data Selection for Efficient Pretraining

Orthogonal Spatial-temporal Distributional Transfer for 4D Generation

DragNeXt: Rethinking Drag-Based Image Editing

Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection

Dr.V : A Hierarchical Perception-Temporal-Cognition Framework to Diagnose Video Hallucination by Fine-Grained Spatial-Temporal Grounding

M$^{3}$3D: A Multimodal, Multilingual and Multitask Dataset for Grounded Document-Level Information Extraction

Evaluating and Mitigating Relationship Hallucinations in Large Vision-Language Models

S HARING B EYOND D ECISION : Deep Collaboration between Large Language Models via Representation Ensemble

Grounding is All You Need? Dual Temporal Grounding for Video Dialog

VEGAS: Towards Visually Explainable and Grounded Artificial Social Intelligence

Time-Frequency Token Advantage Clipping for Training Efficient Large Reasoning Model

CogniTrust: Cognitive Memory-Driven Verifiable Supervision for Robust Hashing

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization

Lightning Fast Caching-based Parallel Denoising Prediction for Accelerating Talking Head Generation

Free-Form Scene Editor: Enabling Multi-Round Object Manipulation Like in a 3D Engine

Bridging the Tokenizer Gap: Semantics and Distribution-aware Knowledge Transfer for Unbiased Cross-Tokenizer Distillation

SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs

Powering Verifiable Learning via Automated Evolutionary Data Synthesis

The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models

MemGuide: Intent-Driven Memory Selection for Goal-Oriented Multi-Session LLM Agents

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models

Mitigating Context Interference for Reliable and Efficient Search Agents

Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors

EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems

Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

Dynamic Soft Contrastive Learning for Spatio-Temporal Forecasting

Retrieving on a topic graph for long document question answering

Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models

Language Reconstruction with Brain Predictive Coding from fMRI Data

Individual Turing Test: A Case Study of LLM-based Simulation Using Longitudinal Personal Data

SurGE: A Benchmark and Evaluation Framework for Scientific Survey Generation

SimVBG: Simulating Individual Values by Backstory Generation

Learning LLM-as-a-Judge for Preference Alignment

Understanding the Effect of Opinion Polarization in Short Video Browsing

Parametric Retrieval Augmented Generation

Brain Image Reconstruction with Retrieval-Augmented Diffusion

Query Augmentation with Brain Signals

EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation

Efficient Paths and Dense Rewards: Probabilistic Flow Reasoning for Large Language Models

Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching

Economic Perspectives on Fairness in Information Retrieval

Fairness in Information Retrieval: An Economic Perspective

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

QE-RAG: A Robust Retrieval-Augmented Generation Benchmark for Query Entry Errors

Counteracting the Delayed Conversions in OCPC with Survival Analysis

Room Matters: Dynamic Room-level Collaboration Information Modeling for Live Streaming Recommendation

Unveiling and Simulating Short-Video Addiction Behaviors via Economic Addiction Theory