SPRINT: Scalable and Predictive Intent Refinement for LLM-Enhanced Session-based Recommendation
sigir26-231 · Full research paper · Gyuseok Lee, Wonbin Kweon, Zhenrui Yue, Yaokun Liu, Yifan Liu, Susik Yoon, Dong Wang, SeongKu Kang
Efficiency and Deployment · 25% Sequential and Session-based Recomme · 25% Efficient and Long-Sequence Sequenti · 12% LLM-Enhanced Sequential Recommendati · 12%
Abstract
Large language models (LLMs) have enhanced conventional recommendation models via user profiling, which generates representative textual profiles from users' historical interactions. However, their direct application to session-based recommendation (SBR) remains challenging due to severe session context scarcity and poor scalability. In this paper, we propose SPRINT, a scalable SBR framework that incorporates reliable and informative intents while ensuring high efficiency in both training and inference. SPRINT constrains LLM-based profiling with a global intent pool and validates inferred intents based on recommendation performance to mitigate noise and hallucinations under limited context. To ensure scalability, LLMs are selectively invoked only for uncertain sessions during training, while a lightweight intent predictor generalizes intent prediction to all sessions without LLM dependency at inference time. Experiments on real-world datasets show that SPRINT consistently outperforms state-of-the-art methods while providing more explainable recommendations.
Assigned reviewers
| # | Reviewer | Match | Why (closest evidence publications in the taxonomy) | |
|---|---|---|---|---|
| 1 | Jie Jiang 0015 | 53 | 77 Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models (2025) Sequential and Session-based Recommendation 76 Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning (2026) Generative Recommendation and Item Tokenization 63 HIT: Learning a Hierarchical Tree-Based Model with Variable-Length Layers for Recommendation Systems (2023) Efficient and Long-Sequence Sequential Recommendation |
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| 2 | Min Hou 0004 | 52 | 87 WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging (2026) Efficiency and Deployment 64 RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation (2026) Preference Alignment and Optimization 52 Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective (2025) Contrastive and Self-Supervised Sequential Recommendation |
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| 3 | James Caverlee | 52 | 84 Language Models as Semantic Augmenters for Sequential Recommenders (2026) Sequential and Session-based Recommendation 57 Consistency-Aware Recommendation for User-Generated Item List Continuation (2020) Multimodal Recommendation for Domain Applications 54 Sequential Recommendation for Cold-start Users with Meta Transitional Learning (2021) Sequential Recommendation with User Modeling and Profiling |
Area chair
| Area chair | Match | |
|---|---|---|
| Maolin Wang 0001 | 58 |
Area-chair candidates (6)
| Maolin Wang 0001 assigned | 58 | 15 papers | |
| Pengyue Jia | 58 | 10 papers | |
| Yanan Niu | 53 | 15 papers | |
| Kun Gai | 53 | 5 papers | |
| Leyu Lin | 51 | 15 papers | |
| Xin Xin 0003 COI: co-author | 50 | 10 papers |
Candidates from the panel ranked by match score
| # | Reviewer | Match | Load | Why | |
|---|---|---|---|---|---|
| 1 | Bo Chen 0023 COI: co-author | 68 | 3 | 83 ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation (2024) Sequential and Session-based Recommendation 83 Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation (2026) Sequential and Session-based Recommendation |
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| 2 | Bo Peng 0009 | 62 | 3 | 64 eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data (2024) Efficiency and Deployment 63 M2: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation (2023) Efficient and Long-Sequence Sequential Recommendation |
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| 3 | Jianling Wang | 60 | 3 | 73 LLMs for User Interest Exploration in Large-scale Recommendation Systems (2024) Sequential and Session-based Recommendation 70 Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs (2024) Efficiency and Deployment |
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| 4 | Jieming Zhu COI: co-author | 60 | 3 | 74 ROMA: Recommendation-Oriented Language Model Adaptation Using Multi-Modal Multi-Domain Item Sequences (2025) Sequential and Session-based Recommendation 71 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment |
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| 7 | Zhengyi Yang 0007 | 57 | 3 | 65 LLaRA: Large Language-Recommendation Assistant (2024) Sequential and Session-based Recommendation 55 A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems (2025) Generative Recommendation and Item Tokenization |
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| 8 | Bowen Zheng 0005 | 57 | 3 | 78 Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation (2025) Sequential and Session-based Recommendation 55 Reciprocal Sequential Recommendation (2023) Sequential Recommendation with User Modeling and Profiling |
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| 9 | Hao Liu 0078 | 56 | 3 | 84 WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging (2026) Efficiency and Deployment 52 Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective (2025) Contrastive and Self-Supervised Sequential Recommendation |
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| 10 | Chongming Gao | 55 | 3 | 66 Large Language Models are Learnable Planners for Long-Term Recommendation (2024) Preference Alignment and Optimization 63 Tunable LLM-based Proactive Recommendation Agent (2025) Preference Alignment and Optimization |
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| 11 | Yang Zhang 0072 | 55 | 3 | 64 Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems (2024) Efficiency and Deployment 61 AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignment (2026) Efficiency and Deployment |
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| 12 | Wei Guo 0006 COI: co-author | 55 | 3 | 71 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment 59 Breaking the Bottleneck: User-Specific Optimization and Real-Time Inference Integration for Sequential Recommendation (2025) Efficient and Long-Sequence Sequential Recommendation |
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| 13 | Jizhi Zhang | 55 | 3 | 64 Navigating Large Language Models for Recommendation: From Architecture to Learning Paradigms and Deployment (2025) Efficiency and Deployment 60 Large Language Model Can Interpret Latent Space of Sequential Recommender (2026) Sequential and Session-based Recommendation |
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| 14 | Fei Sun 0001 | 54 | 3 | 58 LoRec: Combating Poisons with Large Language Model for Robust Sequential Recommendation (2024) Robustness to Noise and Distribution Shift 55 XDM: Improving Sequential Deep Matching with Unclicked User Behaviors for Recommender System (2022) Sequential Recommendation with User Modeling and Profiling |
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| 15 | Junjie Zhang 0009 | 54 | 3 | 64 Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis (2025) Efficiency and Deployment 64 Large Language Models are Zero-Shot Rankers for Recommender Systems (2024) Efficiency and Deployment |
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| 16 | Jiancan Wu | 54 | 3 | 77 LLaRA: Large Language-Recommendation Assistant (2024) Sequential and Session-based Recommendation 77 Large Language Model Can Interpret Latent Space of Sequential Recommender (2026) Sequential and Session-based Recommendation |
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| 17 | Seongmin Park 0002 | 54 | 3 | 61 Temporal Linear Item-Item Model for Sequential Recommendation (2025) Efficient and Long-Sequence Sequential Recommendation 55 MUFFIN: Mixture of User-Adaptive Frequency Filtering for Sequential Recommendation (2025) Sequential Recommendation with User Modeling and Profiling |
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| 18 | Junwei Pan | 53 | 3 | 76 Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning (2026) Generative Recommendation and Item Tokenization 67 Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs (2025) Generative Recommendation and Item Tokenization |
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| 20 | Qijiong Liu | 53 | 3 | 75 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment 60 ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models (2024) LLM-Derived Knowledge Infusion |
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| 21 | Han Li 0005 | 53 | 3 | 78 Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation (2025) Sequential and Session-based Recommendation 59 LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application (2025) Efficiency and Deployment |
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| 23 | Jie Jiang 0015 assigned | 53 | 3 | 77 Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models (2025) Sequential and Session-based Recommendation 76 Cross-Scale Collaboration between LLMs and Lightweight Sequential Recommenders with Domain-Specific Latent Reasoning (2026) Generative Recommendation and Item Tokenization |
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| 24 | Huifeng Guo | 52 | 3 | 66 LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations (2025) Generative Recommendation and Item Tokenization 61 Prompt Tuning as User Inherent Profile Inference Machine (2025) Efficiency and Deployment |
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| 25 | Shuchang Liu 0001 | 52 | 3 | 61 DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems (2025) Preference Alignment and Optimization 59 Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) (2022) Knowledge Infusion and Open-World Augmentation |
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| 26 | Xiao Zhang 0034 | 52 | 3 | 65 MoRE: A Mixture of Reflectors Framework for Large Language Model-Based Sequential Recommendation (2025) Sequential and Session-based Recommendation 55 Large Language Models Enhanced Collaborative Filtering (2024) Preference Alignment and Optimization |
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| 27 | Min Hou 0004 assigned | 52 | 3 | 87 WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging (2026) Efficiency and Deployment 64 RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation (2026) Preference Alignment and Optimization |
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| 28 | Xuanhua Yang | 52 | 3 | 67 Breaking the Relevance-Diversity Seesaw: Hierarchical LLM Reasoning with RL for Industrial Novelty Recommendation (2026) Preference Alignment and Optimization 54 Hierarchical User Long-term Behavior Modeling for Click-Through Rate Prediction (2025) CTR and Conversion Rate Prediction |
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| 29 | James Caverlee assigned | 52 | 3 | 84 Language Models as Semantic Augmenters for Sequential Recommenders (2026) Sequential and Session-based Recommendation 57 Consistency-Aware Recommendation for User-Generated Item List Continuation (2020) Multimodal Recommendation for Domain Applications |
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| 31 | Chen Wang 0052 | 51 | 3 | 63 Cluster-Aware Item Prompt Learning for Session-Based Recommendation (2025) LLM-Enhanced Sequential Recommendation 54 Confidence-Aware Fine-Tuning of Sequential Recommendation Systems Via Conformal Prediction (2025) Contrastive and Self-Supervised Sequential Recommendation |
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| 32 | Yang Song 0008 | 51 | 3 | 54 Mixed Attention Network for Cross-domain Sequential Recommendation (2024) Cross-Domain and Cross-Market Sequential Recommendation 54 Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System (2023) Multi-Behavior and Multi-Interest Sequential Recommendation |
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| 33 | Lantao Hu | 51 | 3 | 55 Modeling User Fatigue for Sequential Recommendation (2024) Contrastive and Self-Supervised Sequential Recommendation 53 Unsupervised Ranking Ensemble Model for Recommendation (2024) Recommendation with Search and Ranking |
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| 35 | Yongjing Hao | 50 | 3 | 55 Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential Recommendation (2023) Contrastive and Self-Supervised Sequential Recommendation 53 Learnable Model Augmentation Contrastive Learning for Sequential Recommendation (2024) Contrastive and Self-Supervised Sequential Recommendation |
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| 36 | Yupeng Hou | 49 | 3 | 72 Large Language Models are Zero-Shot Rankers for Recommender Systems (2024) Efficiency and Deployment 53 Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation (2024) Collaborative-Semantic Representation Alignment |