mlsanityData to 7 Oct 2026

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation

arXiv 2305.00447 ↗First posted 30 Apr 2023cs.IRcited by 336

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Cited by 29 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large Language Models (LLMs) have demonstrated remarkable performance across diverse domains, thereby prompting researchers to explore their potential for use in recommendation systems. Initial attempts have leveraged the exceptional capabilities of LLMs, such as rich knowledge and strong generalization through In-context Learning, which involves phrasing the recommendation task as prompts. Nevertheless, the performance of LLMs in recommendation tasks remains suboptimal due to a substantial disparity between the training tasks for LLMs and recommendation tasks, as well as inadequate recommendation data during pre-training. To bridge the gap, we consider building a Large Recommendation Language Model by tunning LLMs with recommendation data. To this end, we propose an efficient and effective Tuning framework for Aligning LLMs with Recommendation, namely TALLRec. We have demonstrated that the proposed TALLRec framework can significantly enhance the recommendation capabilities of LLMs in the movie and book domains, even with a limited dataset of fewer than 100 samples. Additionally, the proposed framework is highly efficient and can be executed on a single RTX 3090 with LLaMA-7B. Furthermore, the fine-tuned LLM exhibits robust cross-domain generalization. Our code and data are available at https://github.com/SAI990323/TALLRec.

Key facts. Cited by 336 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Apr 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 33; 2024: 94; 2025: 110; 2026: 99.

336 papers.

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  1. 2023A Survey on Large Language Models for Recommendationcited by 378
  2. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  3. 2024From Persona to Personalization: A Survey on Role-Playing Language Agentscited by 206
  4. 2023Recommender Systems in the Era of Large Language Models (LLMs)cited by 188
  5. 2024Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendationscited by 184
  6. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  7. 2023Representation Learning with Large Language Models for Recommendationcited by 155
  8. 2025Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMscited by 142
  9. 2023How Can Recommender Systems Benefit from Large Language Models: A Surveycited by 141
  10. 2023RecMind: Large Language Model Powered Agent For Recommendationcited by 129
  11. 2023Large Language Models as Zero-Shot Conversational Recommenderscited by 126
  12. 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systemscited by 116
38 more
  1. 2023Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendationcited by 113
  2. 2023Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspectivecited by 91
  3. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 89
  4. 2023ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendationcited by 76
  5. 2023Large Language Models for Generative Recommendation: A Survey and Visionary Discussionscited by 72
  6. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  7. 2024HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modelingcited by 63
  8. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  9. 2024GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capabilitycited by 57
  10. 2025Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendationcited by 56
  11. 2024Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender Systemcited by 50
  12. 2025A Survey on LLM-powered Agents for Recommender Systemscited by 49
  13. 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendationcited by 47
  14. 2023Exploring Large Language Model for Graph Data Understanding in Online Job Recommendationscited by 45
  15. 2024CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendationcited by 44
  16. 2025Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalizationcited by 44
  17. 2025PersonaLens: A Benchmark for Personalization Evaluation in Conversational AI Assistantscited by 44
  18. 2023Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generationcited by 42
  19. 2025A Survey on Personalized Alignment -- The Missing Piece for Large Language Models in Real-World Applicationscited by 40
  20. 2023E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendationcited by 39
  21. 2024TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendationcited by 35
  22. 2024Graph Machine Learning in the Era of Large Language Models (LLMs)cited by 33
  23. 2024Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendationcited by 33
  24. 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendationcited by 32
  25. 2025Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learningcited by 32
  26. 2023RAH! RecSys-Assistant-Human: A Human-Centered Recommendation Framework with LLM Agentscited by 30
  27. 2023Large Language Models for Intent-Driven Session Recommendationscited by 30
  28. 2023Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Communitycited by 29
  29. 2023Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answeringcited by 28
  30. 2023ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Predictioncited by 27
  31. 2023DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendationcited by 27
  32. 2024Rethinking Large Language Model Architectures for Sequential Recommendationscited by 27
  33. 2024IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFTcited by 26
  34. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  35. 2024Large Language Model Distilling Medication Recommendation Modelcited by 25
  36. 2024How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendationcited by 25
  37. 2024LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendationscited by 24
  38. 2024Unified Parameter-Efficient Unlearning for LLMscited by 24

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