mlsanityData to 7 Oct 2026

AgentCF++: Memory-enhanced LLM-based Agents for Popularity-aware Cross-domain Recommendations

arXiv 2502.13843 ↗First posted 19 Feb 2025cs.IR cs.AIcited by 23

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

Abstract (arXiv)

LLM-based user agents, which simulate user interaction behavior, are emerging as a promising approach to enhancing recommender systems. In real-world scenarios, users' interactions often exhibit cross-domain characteristics and are influenced by others. However, the memory design in current methods causes user agents to introduce significant irrelevant information during decision-making in cross-domain scenarios and makes them unable to recognize the influence of other users' interactions, such as popularity factors. To tackle this issue, we propose a dual-layer memory architecture combined with a two-step fusion mechanism. This design avoids irrelevant information during decision-making while ensuring effective integration of cross-domain preferences. We also introduce the concepts of interest groups and group-shared memory to better capture the influence of popularity factors on users with similar interests. Comprehensive experiments validate the effectiveness of AgentCF++. Our code is available at https://github.com/jhliu0807/AgentCF-plus.

Key facts. Cited by 23 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 30 of its 50 references that are in the map. First posted on arXiv 19 Feb 2025.

Builds on

30 of 50 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024Prospect Personalized Recommendation on Large Language Model-based Agent Platform28 Feb
  2. 2023On Generative Agents in Recommendation16 Oct
  3. 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems13 Oct
  4. 2023Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations31 Aug
  5. 2023RAH! RecSys-Assistant-Human: A Human-Centered Recommendation Framework with LLM Agents19 Aug

Other references · 25

  1. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  2. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  3. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  4. 2018Self-Attentive Sequential Recommendationcited by 1,169
  5. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  6. 2024Understanding the planning of LLM agents: A surveycited by 414
  7. 2023TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendationcited by 336
  8. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  9. 2023Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategiescited by 236
  10. 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 213
  11. 2023Leveraging Large Language Models for Sequential Recommendationcited by 78
  12. 2024Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learningcited by 51
13 more
  1. 2022A Survey on Trustworthy Recommender Systemscited by 40
  2. 2024LLM-Powered User Simulator for Recommender Systemcited by 38
  3. 2021A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directionscited by 30
  4. 2023Personalized Graph Signal Processing for Collaborative Filteringcited by 29
  5. 2024Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recencycited by 27
  6. 2024How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendationcited by 25
  7. 2024Large Language Models as Recommender Systems: A Study of Popularity Biascited by 25
  8. 2024Large Language Models are Learnable Planners for Long-Term Recommendationcited by 24
  9. 2024Item-side Fairness of Large Language Model-based Recommendation Systemcited by 21
  10. 2024Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendationcited by 19
  11. 2023AutoSeqRec: Autoencoder for Efficient Sequential Recommendationcited by 15
  12. 2022Parameter-free Dynamic Graph Embedding for Link Predictioncited by 12
  13. 2023Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendationcited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 21.

23 papers.

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By area:

  1. 2025Memory in the Age of AI Agentscited by 285
  2. 2026Graph-based Agent Memory: Taxonomy, Techniques, and Applicationscited by 22
  3. 2026HiMem: Hierarchical Long-Term Memory for LLM Long-Horizon Agentscited by 16
  4. 2026RecNet: Self-Evolving Preference Propagation for Agentic Recommender Systemscited by 6
  5. 2026From Atom to Community: Structured and Evolving Agent Memory for User Behavior Modelingcited by 3
  6. 2026Autonomous Information Seeking: A Roadmap for Agentic Recommender Systemscited by 3
  7. 2025Quantifying the Potential to Escape Filter Bubbles: A Behavior-Aware Measure via Contrastive Simulationcited by 2
  8. 2026From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agentscited by 2
  9. 2026Seeing and Reflecting: Multimodal Memory-Enhanced Agent Collaboration for Recommendationcited by 2
  10. 2026Enhancing Conversational Agents via Task-Oriented Adversarial Memory Adaptationcited by 1
  11. 2026RQ-GMM: Residual Quantized Gaussian Mixture Model for Multimodal Semantic Discretization in CTR Predictioncited by 1
  12. 2026Self-Distilled Reinforcement Learning for Co-Evolving Agentic Recommender Systemscited by 1
11 more
  1. 2026Learning from Online User Feedback for Shopping Agentscited by 1
  2. 2026Position: Recommender Systems Should Move Beyond Platform-Centric Ranking toward Personal Agent-Mediated Recommendationcited by 1
  3. 2026Distribution-Aware End-to-End Embedding for Streaming Numerical Features in Click-Through Rate Predictioncited by 0
  4. 2026TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendationcited by 0
  5. 2026Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivitycited by 0
  6. 2026Personalized Communication Skills for Agentic Recommender Systemscited by 0
  7. 2026ElderBench: Benchmarking Autonomous Mobile Agents for Older Adultscited by 0
  8. 2026AgentRecommender: LLM Agents Enable Customizable Recommender Systems on the User Sidecited by 0
  9. 2026ReMem: Rethinking Perception and Memory in Long-Context Recommendation Agentscited by 0
  10. 2026VirusCascade: Hijacking Collaborative Reflection in LLM-Powered Recommender Agentscited by 0
  11. 2026AgentWebRec: Compact Evidence Fusion over the Agent Web for Personalized Recommendationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026AMEM4Rec: Leveraging Cross-User Similarity for Memory Evolution in Agentic LLM Recommenders
  2. 2026MemRec: Collaborative Memory-Augmented Agentic Recommender System
  3. 2025Multi-Agent Collaborative Filtering: Orchestrating Users and Items for Agentic Recommendations
  4. 2026Enhancing Group Recommendation with Memory-Augmented Reasoning in LLM Agent
  5. 2026Agentic Recommender System with Hierarchical Belief-State Memory
  6. 2026When Memory Takes Gradients: Collaborative Vector Memory for Agentic Recommender Systems
  7. 2026Learning from Others, Acting for You: Cross-User Memory Sharing for LLM Agents
  8. 2025A Survey on LLM-powered Agents for Recommender Systems