Verbalizing LightGCN: Direct Learning of Textual Representations from User-Item Interaction Graph via LLMs
sigir26-097 · Full research paper · Manh-Khanh Ngo Huu, Hady Wirawan Lauw
LLM-Collaborative Filtering Integrat · 25% Graph Neural Network Architectures f · 25% User Profile and Persona Modeling · 25% LLM-Derived Knowledge Infusion · 25%
Abstract
In this work, we propose VerbaLightGCN, a novel LLM-based recommendation framework that integrates the semantic understanding of LLMs with user-item interaction modeling. Traditional collaborative filtering (CF) models typically embed user and item IDs into a latent space to capture interaction signals. However, pretrained LLMs cannot natively interpret these learned embeddings. To bridge this gap, VerbaLightGCN adopts a CF-as-text paradigm, in which collaborative signals are encoded in textual form and directly learned from the user–item interaction graph, and are then combined with semantic information to construct user and item profiles that function as latent embeddings. Inspired by LightGCN, our method retains its message-passing design but replaces numerical embedding computations with a Chain-of-Thought prompting mechanism. This enables LLMs to simulate the LightGCN aggregation process through natural language. The result is a recommendation framework that unifies semantic understanding with collaborative signals in a fully language-native form. Experiments show that VerbaLightGCN achieves superior performance to both zero-shot LLM-based and traditional CF-based baselines. Further analysis reveals that the user and item profiles generated by VerbaLightGCN effectively capture both semantic preferences and collaborative filtering signals.
Assigned reviewers
| # | Reviewer | Match | Why (closest evidence publications in the taxonomy) | |
|---|---|---|---|---|
| 1 | Huifeng Guo | 52 | 60 Prompt Tuning as User Inherent Profile Inference Machine (2025) Efficiency and Deployment 56 Compressed Interaction Graph based Framework for Multi-behavior Recommendation (2023) Sequential and Session-Based Graph Recommendation 56 SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems (2025) LLM-Derived Knowledge Infusion |
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| 2 | Xiaolong Liu 0012 | 50 | 56 DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation (2023) Graph-based User and Item Representation Learning 55 Collaborative Alignment for Recommendation (2024) Graph Contrastive and Self-Supervised Learning 53 Unified Pretraining for Recommendation via Task Hypergraphs (2024) Graph Neural Network Architectures for CF |
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| 3 | Jin Chen 0008 | 49 | 54 When large language models meet personalization: perspectives of challenges and opportunities (2024) User Profile and Persona Modeling 48 Cooperative Retriever and Ranker in Deep Recommenders (2023) Recommendation with Search and Ranking 48 Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation (2024) Recommendation Systems and Evaluation |
Area chair
| Area chair | Match | |
|---|---|---|
| Pengyue Jia | 49 |
Area-chair candidates (7)
| Pengyue Jia assigned | 49 | 10 papers | |
| Xin Xin 0003 | 49 | 10 papers | |
| Yankai Chen 0001 | 47 | 6 papers | |
| Maolin Wang 0001 | 47 | 15 papers | |
| Yanan Niu | 46 | 15 papers | |
| Kun Gai | 45 | 5 papers | |
| Weiming Liu 0005 | 44 | 8 papers |
Candidates from the panel ranked by match score
| # | Reviewer | Match | Load | Why | |
|---|---|---|---|---|---|
| 1 | Bo Chen 0023 | 53 | 3 | 74 ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation (2024) LLM-Collaborative Filtering Integration 67 Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation (2026) Sequential and Session-based Recommendation |
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| 2 | Huifeng Guo assigned | 52 | 3 | 60 Prompt Tuning as User Inherent Profile Inference Machine (2025) Efficiency and Deployment 56 Compressed Interaction Graph based Framework for Multi-behavior Recommendation (2023) Sequential and Session-Based Graph Recommendation |
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| 3 | Yongjing Hao | 51 | 3 | 56 How Do Graph Signals Affect Recommendation: Unveiling the Mystery of Low and High-Frequency Graph Signals (2026) Graph-based User and Item Representation Learning 56 Edge-enhanced Global Disentangled Graph Neural Network for Sequential Recommendation (2023) Sequential and Session-Based Graph Recommendation |
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| 4 | Yang Zhang 0072 | 50 | 3 | 60 AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignment (2026) Efficiency and Deployment 54 LLM Personalization: Foundations, Breakthroughs, and Frontiers (2026) User Profile and Persona Modeling |
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| 5 | Xiaolong Liu 0012 assigned | 50 | 3 | 56 DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation (2023) Graph-based User and Item Representation Learning 55 Collaborative Alignment for Recommendation (2024) Graph Contrastive and Self-Supervised Learning |
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| 6 | Jizhi Zhang | 50 | 3 | 54 Agentic Feedback Loop Modeling Improves Recommendation and User Simulation (2025) User Profile and Persona Modeling 51 Large Language Model Can Interpret Latent Space of Sequential Recommender (2026) Sequential and Session-based Recommendation |
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| 7 | Jiancan Wu | 50 | 3 | 56 Graph convolution machine for context-aware recommender system (2022) Graph-based User and Item Representation Learning 56 Large Language Model Can Interpret Latent Space of Sequential Recommender (2026) Sequential and Session-based Recommendation |
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| 8 | Jieming Zhu | 49 | 3 | 60 Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models (2024) Knowledge Infusion and Open-World Augmentation 59 Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models (2026) Knowledge Infusion and Open-World Augmentation |
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| 10 | Seongmin Park 0002 | 49 | 3 | 60 LLM-Enhanced Linear Autoencoders for Recommendation (2025) Collaborative-Semantic Representation Alignment 50 Linear Item-Item Models with Neural Knowledge for Session-based Recommendation (2025) Efficient and Long-Sequence Sequential Recommendation |
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| 12 | Jin Chen 0008 assigned | 49 | 3 | 54 When large language models meet personalization: perspectives of challenges and opportunities (2024) User Profile and Persona Modeling 48 Cooperative Retriever and Ranker in Deep Recommenders (2023) Recommendation with Search and Ranking |
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| 13 | Bowen Zheng 0005 | 49 | 3 | 52 Autonomous Reasoning-Retrieval for Large Language Model Based Recommendation (2025) Reasoning-Intensive Retrieval and Ranking 50 Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation (2024) Generative Recommendation and Item Tokenization |
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| 14 | Jianling Wang | 48 | 3 | 59 LLMs for User Interest Exploration in Large-scale Recommendation Systems (2024) Sequential and Session-based Recommendation 58 Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs (2024) Efficiency and Deployment |
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| 15 | Chongming Gao | 48 | 3 | 54 Agentic Feedback Loop Modeling Improves Recommendation and User Simulation (2025) User Profile and Persona Modeling 48 On the Theories Behind Hard Negative Sampling for Recommendation (2023) Recommendation Systems and Evaluation |
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| 16 | Xiao Zhang 0034 | 48 | 3 | 61 Benefit from Rich: Tackling Search Interaction Sparsity in Search Enhanced Recommendation (2025) Recommendation with Search and Ranking 58 Large Language Models Enhanced Collaborative Filtering (2024) Preference Alignment and Optimization |
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| 17 | Zhengyi Yang 0007 | 48 | 3 | 50 Large Language Model Can Interpret Latent Space of Sequential Recommender (2026) Generative Recommendation and Item Tokenization 47 A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems (2025) Generative Recommendation and Item Tokenization |
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| 19 | Wei Wei 0027 | 47 | 3 | 68 LLMRec: Large Language Models with Graph Augmentation for Recommendation (2024) Graph Pretraining and Foundation Models 54 Representation Learning with Large Language Models for Recommendation (2024) Text Embedding and Representation Learning |
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| 21 | Yang Song 0008 | 47 | 3 | 72 Large Language Models Enhanced Collaborative Filtering (2024) LLM-Enhanced Collaborative Filtering 56 Sequential Recommendation with Graph Neural Networks (2021) Sequential and Session-Based Graph Recommendation |
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| 23 | Chen Wang 0052 | 46 | 3 | 57 Unified Pretraining for Recommendation via Task Hypergraphs (2024) Graph Pretraining and Foundation Models 49 Collaborative Alignment for Recommendation (2024) Collaborative-Semantic Representation Alignment |
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| 24 | Fei Sun 0001 | 46 | 3 | 46 Personalized re-ranking for recommendation (2019) Recommendation with Search and Ranking 46 Neural Re-ranking in Multi-stage Recommender Systems: A Review (2022) Recommendation Systems and Evaluation |
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| 25 | Noveen Sachdeva | 46 | 3 | 49 Sequential Variational Autoencoders for Collaborative Filtering (2019) Generative Models for Recommendation and Content › Others 49 ECLARE: Extreme Classification with Label Graph Correlations (2021) Graph Neural Network Architectures for CF |
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| 26 | Bo Peng 0009 | 46 | 3 | 48 eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data (2024) Efficiency and Deployment 48 M2: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation (2023) Efficient and Long-Sequence Sequential Recommendation |
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| 27 | Riwei Lai | 46 | 3 | 60 Multi-Faceted Global Item Relation Learning for Session-Based Recommendation (2022) Graph-Based Sequential and Session Recommendation 46 Proxy-Aware Cross-Domain Sequential Recommendation (2023) Cross-Domain Sequential Recommendation |
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| 28 | Lingling Yi | 46 | 3 | 60 TRAWL: External Knowledge-Enhanced Recommendation with LLM Assistance (2025) LLM-Derived Knowledge Infusion 56 PRECISE: Pre-training and Fine-tuning Sequential Recommenders with Collaborative and Semantic Information (2025) Sequential and Session-based Recommendation |
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| 29 | Qijiong Liu | 46 | 3 | 60 ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models (2024) LLM-Derived Knowledge Infusion 48 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment |
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| 30 | Junjie Zhang 0009 | 46 | 3 | 53 STARec: An Efficient Agent Framework for Recommender Systems via Autonomous Deliberate Reasoning (2025) RL Training of Search Agents 52 AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems (2024) RL Training of Search Agents |
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| 31 | Wei Guo 0006 | 45 | 3 | 56 Compressed Interaction Graph based Framework for Multi-behavior Recommendation (2023) Sequential and Session-Based Graph Recommendation 49 Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation (2025) Efficiency and Deployment |
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| 33 | Han Li 0005 | 45 | 3 | 50 LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application (2025) Efficiency and Deployment 47 Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation (2025) Sequential and Session-based Recommendation |
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| 34 | Shuchang Liu 0001 | 45 | 3 | 55 Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) (2022) Knowledge Infusion and Open-World Augmentation 49 DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems (2025) Preference Alignment and Optimization |
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| 35 | Min Hou 0004 | 45 | 3 | 62 STGCN: A Spatial-Temporal Aware Graph Learning Method for POI Recommendation (2020) Graph Neural Network Architectures for CF 49 WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging (2026) Efficiency and Deployment |
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| 37 | Lianghao Xia | 44 | 3 | 58 RecLM: Recommendation Instruction Tuning (2025) Preference Alignment and Optimization 51 Self-Supervised Hypergraph Transformer for Recommender Systems (2022) Graph Contrastive and Self-Supervised Learning |