mlsanityData to 7 Oct 2026

CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation

arXiv 2310.19488 ↗First posted 30 Oct 2023cs.IRcited by 99

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Abstract (arXiv)

Leveraging Large Language Models as Recommenders (LLMRec) has gained significant attention and introduced fresh perspectives in user preference modeling. Existing LLMRec approaches prioritize text semantics, usually neglecting the valuable collaborative information from user-item interactions in recommendations. While these text-emphasizing approaches excel in cold-start scenarios, they may yield sub-optimal performance in warm-start situations. In pursuit of superior recommendations for both cold and warm start scenarios, we introduce CoLLM, an innovative LLMRec methodology that seamlessly incorporates collaborative information into LLMs for recommendation. CoLLM captures collaborative information through an external traditional model and maps it to the input token embedding space of LLM, forming collaborative embeddings for LLM usage. Through this external integration of collaborative information, CoLLM ensures effective modeling of collaborative information without modifying the LLM itself, providing the flexibility to employ various collaborative information modeling techniques. Extensive experiments validate that CoLLM adeptly integrates collaborative information into LLMs, resulting in enhanced recommendation performance. We release the code and data at https://github.com/zyang1580/CoLLM.

Key facts. Cited by 99 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Oct 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 32; 2025: 38; 2026: 29.

99 papers.

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  1. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  2. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  3. 2025Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendationcited by 56
  4. 2025A Survey on LLM-powered Agents for Recommender Systemscited by 49
  5. 2024CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendationcited by 44
  6. 2025Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalizationcited by 44
  7. 2024TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendationcited by 35
  8. 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendationcited by 32
  9. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  10. 2024LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendationscited by 24
  11. 2024Review-driven Personalized Preference Reasoning with Large Language Models for Recommendationcited by 20
  12. 2025Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMscited by 20
38 more
  1. 2025Latent Inter-User Difference Modeling for LLM Personalizationcited by 20
  2. 2024Stealthy Attack on Large Language Model based Recommendationcited by 19
  3. 2024SLMRec: Distilling Large Language Models into Small for Sequential Recommendationcited by 18
  4. 2024Language Representations Can be What Recommenders Need: Findings and Potentialscited by 18
  5. 2025ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendationcited by 18
  6. 2024Towards Efficient and Effective Unlearning of Large Language Models for Recommendationcited by 16
  7. 2024A Survey of Generative Search and Recommendation in the Era of Large Language Modelscited by 14
  8. 2024Towards Graph Foundation Models for Personalizationcited by 12
  9. 2025Uncertainty Quantification and Decomposition for LLM-based Recommendationcited by 12
  10. 2025DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agentscited by 12
  11. 2024Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Reviewcited by 11
  12. 2025LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendationcited by 11
  13. 2024EasyRec: Simple yet Effective Language Models for Recommendationcited by 10
  14. 2024End-to-end Training for Recommendation with Language-based User Profilescited by 10
  15. 2025CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendationcited by 10
  16. 2024Semantic Convergence: Harmonizing Recommender Systems via Two-Stage Alignment and Behavioral Semantic Tokenizationcited by 9
  17. 2024Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendationcited by 8
  18. 2025Lost in Sequence: Do Large Language Models Understand Sequential Recommendation?cited by 8
  19. 2025RecGPT-V2 Technical Reportcited by 8
  20. 2024Item-Language Model for Conversational Recommendationcited by 7
  21. 2024Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM Optimizerscited by 7
  22. 2024CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendationcited by 7
  23. 2024Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendationcited by 7
  24. 2025From Prompting to Alignment: A Generative Framework for Query Recommendationcited by 7
  25. 2025GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusioncited by 7
  26. 2025TrackRec: Iterative Alternating Feedback with Chain-of-Thought via Preference Alignment for Recommendationcited by 7
  27. 2025Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learningcited by 7
  28. 2024Towards Incremental Learning in Large Language Models: A Critical Reviewcited by 6
  29. 2025EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integrationcited by 6
  30. 2025Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Modelcited by 6
  31. 2024Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learningcited by 5
  32. 2024Bridging Conversational and Collaborative Signals for Conversational Recommendationcited by 5
  33. 2025Fine-grained List-wise Alignment for Generative Medication Recommendationcited by 5
  34. 2025IGD: Token Decisiveness Modeling via Information Gain in LLMs for Personalized Recommendationcited by 5
  35. 2024Integrating Large Language Models with Graphical Session-Based Recommendationcited by 4
  36. 2024Collaborative Cross-modal Fusion with Large Language Model for Recommendationcited by 4
  37. 2024Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Modelscited by 4
  38. 2025Large Language Model as Universal Retriever in Industrial-Scale Recommender Systemcited by 4

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