mlsanityData to 7 Oct 2026

AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems

arXiv 2310.09233 ↗First posted 13 Oct 2023cs.IR cs.CLcited by 116

On the map: LLM agents and tool use → Agentic recommender systems

Abstract (arXiv)

Recently, there has been an emergence of employing LLM-powered agents as believable human proxies, based on their remarkable decision-making capability. However, existing studies mainly focus on simulating human dialogue. Human non-verbal behaviors, such as item clicking in recommender systems, although implicitly exhibiting user preferences and could enhance the modeling of users, have not been deeply explored. The main reasons lie in the gap between language modeling and behavior modeling, as well as the incomprehension of LLMs about user-item relations. To address this issue, we propose AgentCF for simulating user-item interactions in recommender systems through agent-based collaborative filtering. We creatively consider not only users but also items as agents, and develop a collaborative learning approach that optimizes both kinds of agents together. Specifically, at each time step, we first prompt the user and item agents to interact autonomously. Then, based on the disparities between the agents' decisions and real-world interaction records, user and item agents are prompted to reflect on and adjust the misleading simulations collaboratively, thereby modeling their two-sided relations. The optimized agents can also propagate their preferences to other agents in subsequent interactions, implicitly capturing the collaborative filtering idea. Overall, the optimized agents exhibit diverse interaction behaviors within our framework, including user-item, user-user, item-item, and collective interactions. The results show that these agents can demonstrate personalized behaviors akin to those of real-world individuals, sparking the development of next-generation user behavior simulation.

Key facts. Cited by 116 papers in the map (data through 7 Oct 2026). Placed in Agentic recommender systems, one of 16 directions in LLM agents and tool use. Builds on 52 of its 70 references that are in the map. First posted on arXiv 13 Oct 2023.

Builds on

52 of 70 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023Lending Interaction Wings to Recommender Systems with Conversational Agents6 Oct
  2. 2023Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations31 Aug
  3. 2023RecMind: Large Language Model Powered Agent For Recommendation28 Aug

Other references · 49

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  3. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  4. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  5. 2023A Survey of Large Language Modelscited by 2,537
  6. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  7. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  8. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  9. 2018Self-Attentive Sequential Recommendationcited by 1,169
  10. 2017Neural Collaborative Filteringcited by 1,108
  11. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  12. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debatecited by 724
37 more
  1. 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 580
  2. 2022Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)cited by 396
  3. 2023A Survey on Large Language Models for Recommendationcited by 378
  4. 2023TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendationcited by 336
  5. 2020S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximizationcited by 311
  6. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  7. 2023Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender Systemcited by 241
  8. 2023Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategiescited by 236
  9. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agentscited by 228
  10. 2023Is ChatGPT a Good Recommender? A Preliminary Studycited by 192
  11. 2023Recommender Systems in the Era of Large Language Models (LLMs)cited by 188
  12. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  13. 2023Uncovering ChatGPT's Capabilities in Recommender Systemscited by 160
  14. 2023SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoningcited by 157
  15. 2022M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systemscited by 152
  16. 2023How Can Recommender Systems Benefit from Large Language Models: A Surveycited by 141
  17. 2020RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithmscited by 137
  18. 2022Towards Universal Sequence Representation Learning for Recommender Systemscited by 120
  19. 2023Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Predictioncited by 113
  20. 2023Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendationcited by 113
  21. 2022Learning Vector-Quantized Item Representation for Transferable Sequential Recommenderscited by 112
  22. 2023GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretationcited by 101
  23. 2023PALR: Personalization Aware LLMs for Recommendationcited by 96
  24. 2019RecSim: A Configurable Simulation Platform for Recommender Systemscited by 91
  25. 2023MindAgent: Emergent Gaming Interactioncited by 87
  26. 2023AgentSims: An Open-Source Sandbox for Large Language Model Evaluationcited by 86
  27. 2023ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendationcited by 76
  28. 2023Towards Open-World Recommendation with Knowledge Augmentation from Large Language Modelscited by 74
  29. 2023A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systemscited by 73
  30. 2023Large Language Models for Generative Recommendation: A Survey and Visionary Discussionscited by 72
  31. 2023Zero-Shot Next-Item Recommendation using Large Pretrained Language Modelscited by 53
  32. 2023Enhancing Recommender Systems with Large Language Model Reasoning Graphscited by 52
  33. 2013Empirical Analysis of Predictive Algorithms for Collaborative Filteringcited by 47
  34. 2023Exploring Large Language Model for Graph Data Understanding in Online Job Recommendationscited by 45
  35. 2023Generative Job Recommendations with Large Language Modelcited by 13
  36. 2023ChatLog: Carefully Evaluating the Evolution of ChatGPT Across Timecited by 12
  37. 2022Recent Advances in RecBole: Extensions with more Practical Considerationscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 22; 2025: 45; 2026: 49.

116 papers.

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  1. 2024Large Language Model based Multi-Agents: A Survey of Progress and Challengescited by 752
  2. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  3. 2025Multi-Agent Collaboration Mechanisms: A Survey of LLMscited by 424
  4. 2024Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agentscited by 210
  5. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
  6. 2024Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Eracited by 97
  7. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunitiescited by 83
  8. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agentscited by 76
  9. 2024MACRec: a Multi-Agent Collaboration Framework for Recommendationcited by 58
  10. 2025Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendationcited by 56
  11. 2024Learning to Use Tools via Cooperative and Interactive Agentscited by 54
  12. 2025A Survey on LLM-powered Agents for Recommender Systemscited by 49
38 more
  1. 2025Reinforced Latent Reasoning for LLM-based Recommendationcited by 46
  2. 2024Evaluating Large Language Models as Generative User Simulators for Conversational Recommendationcited by 45
  3. 2024KARMA: Augmenting Embodied AI Agents with Long-and-short Term Memory Systemscited by 38
  4. 2025PersonaX: A Recommendation Agent Oriented User Modeling Framework for Long Behavior Sequencecited by 33
  5. 2025Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systemscited by 32
  6. 2025SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluationcited by 32
  7. 2025A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrievalcited by 31
  8. 2025Towards Agentic Recommender Systems in the Era of Multimodal Large Language Modelscited by 25
  9. 2025AutoData: A Multi-Agent System for Open Web Data Collectioncited by 25
  10. 2024BASES: Large-scale Web Search User Simulation with Large Language Model based Agentscited by 24
  11. 2025AgentCF++: Memory-enhanced LLM-based Agents for Popularity-aware Cross-domain Recommendationscited by 23
  12. 2025iAgent: LLM Agent as a Shield between User and Recommender Systemscited by 23
  13. 2025AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systemscited by 23
  14. 2026Graph-based Agent Memory: Taxonomy, Techniques, and Applicationscited by 22
  15. 2025The Coming Crisis of Multi-Agent Misalignment: AI Alignment Must Be a Dynamic and Social Processcited by 21
  16. 2024MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimizationcited by 20
  17. 2024Prospect Personalized Recommendation on Large Language Model-based Agent Platformcited by 19
  18. 2024Language Representations Can be What Recommenders Need: Findings and Potentialscited by 18
  19. 2024SPRec: Self-Play to Debias LLM-based Recommendationcited by 18
  20. 2025RecoWorld: Building Simulated Environments for Agentic Recommender Systemscited by 18
  21. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  22. 2024Towards Efficient and Effective Unlearning of Large Language Models for Recommendationcited by 16
  23. 2024SheetAgent: Towards A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Modelscited by 16
  24. 2024Agentic Feedback Loop Modeling Improves Recommendation and User Simulationcited by 16
  25. 2026MemRec: Collaborative Memory-Augmented Agentic Recommender Systemcited by 15
  26. 2025AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platformscited by 12
  27. 2025DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agentscited by 12
  28. 2024Knowledge Graph Enhanced Language Agents for Recommendationcited by 11
  29. 2025Slow Thinking for Sequential Recommendationcited by 11
  30. 2024EasyRec: Simple yet Effective Language Models for Recommendationcited by 10
  31. 2025Knowledge is Power: Harnessing Large Language Models for Enhanced Cognitive Diagnosiscited by 10
  32. 2025Multi-Agent Collaborative Filtering: Orchestrating Users and Items for Agentic Recommendationscited by 10
  33. 2026Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directionscited by 10
  34. 2025Improving LLM-powered Recommendations with Personalized Informationcited by 9
  35. 2025Human vs. Agent in Task-Oriented Conversationscited by 9
  36. 2024Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendationcited by 8
  37. 2025Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourismcited by 7
  38. 2026AMEM4Rec: Leveraging Cross-User Similarity for Memory Evolution in Agentic LLM Recommenderscited by 7

50 most cited of 116 All 116 (JSON)

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  1. 2023On Generative Agents in Recommendation
  2. 2025AgentRec: Next-Generation LLM-Powered Multi-Agent Collaborative Recommendation with Adaptive Intelligence
  3. 2026Do Recommendation Algorithms Work When Users Are LLM Agents? A Case Study on Moltbook
  4. 2026Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation
  5. 2025The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systems
  6. 2026AlignUSER: Human-Aligned LLM Agents via World Models for Recommender System Evaluation
  7. 2025RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems
  8. 2026Rethinking Recommendation Paradigms: From Pipelines to Agentic Recommender Systems