mlsanityData to 7 Oct 2026

Improving LLM-powered Recommendations with Personalized Information

arXiv 2502.13845 ↗First posted 19 Feb 2025cs.IR cs.AIcited by 9

On the map: LLM reasoning → LLM reasoning for recommendation

Abstract (arXiv)

Due to the lack of explicit reasoning modeling, existing LLM-powered recommendations fail to leverage LLMs' reasoning capabilities effectively. In this paper, we propose a pipeline called CoT-Rec, which integrates two key Chain-of-Thought (CoT) processes -- user preference analysis and item perception analysis -- into LLM-powered recommendations, thereby enhancing the utilization of LLMs' reasoning abilities. CoT-Rec consists of two stages: (1) personalized information extraction, where user preferences and item perception are extracted, and (2) personalized information utilization, where this information is incorporated into the LLM-powered recommendation process. Experimental results demonstrate that CoT-Rec shows potential for improving LLM-powered recommendations. The implementation is publicly available at https://github.com/jhliu0807/CoT-Rec.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Placed in LLM reasoning for recommendation, one of 17 directions in LLM reasoning. Builds on 43 of its 59 references that are in the map. First posted on arXiv 19 Feb 2025.

Builds on

43 of 59 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Large Language Models Enhanced Collaborative Filtering26 Mar
  2. 2024Can Small Language Models be Good Reasoners for Sequential Recommendation?7 Mar

Other references · 41

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2018Self-Attentive Sequential Recommendationcited by 1,169
  3. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  4. 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 213
  5. 2023LLMRec: Large Language Models with Graph Augmentation for Recommendationcited by 171
  6. 2023Adapting Large Language Models by Integrating Collaborative Semantics for Recommendationcited by 171
  7. 2023Representation Learning with Large Language Models for Recommendationcited by 155
  8. 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systemscited by 116
  9. 2023Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendationcited by 113
  10. 2023Leveraging Large Language Models for Sequential Recommendationcited by 78
  11. 2023ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendationcited by 76
  12. 2023A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systemscited by 73
29 more
  1. 2024On Softmax Direct Preference Optimization for Recommendationcited by 64
  2. 2024HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modelingcited by 63
  3. 2024Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learningcited by 51
  4. 2024Harnessing Large Language Models for Text-Rich Sequential Recommendationcited by 38
  5. 2023RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendationcited by 36
  6. 2024NoteLLM: A Retrievable Large Language Model for Note Recommendationcited by 33
  7. 2023Large Language Models for Intent-Driven Session Recommendationscited by 30
  8. 2023Personalized Graph Signal Processing for Collaborative Filteringcited by 29
  9. 2023ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Predictioncited by 27
  10. 2024Text-like Encoding of Collaborative Information in Large Language Models for Recommendationcited by 25
  11. 2024Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviorscited by 23
  12. 2024Enhancing Recommendation Diversity by Re-ranking with Large Language Modelscited by 19
  13. 2024Large Language Models as Data Augmenters for Cold-Start Item Recommendationcited by 19
  14. 2024Aligning Large Language Models for Controllable Recommendationscited by 19
  15. 2024Aligning Large Language Models with Recommendation Knowledgecited by 19
  16. 2024Large Language Models as Evaluators for Recommendation Explanationscited by 19
  17. 2023Unlocking the Potential of Large Language Models for Explainable Recommendationscited by 18
  18. 2023AutoSeqRec: Autoencoder for Efficient Sequential Recommendationcited by 15
  19. 2024LLMs for User Interest Exploration in Large-scale Recommendation Systemscited by 15
  20. 2023RecExplainer: Aligning Large Language Models for Explaining Recommendation Modelscited by 14
  21. 2023Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendationcited by 12
  22. 2024Enhancing Item Tokenization for Generative Recommendation through Self-Improvementcited by 9
  23. 2023Adaptive In-Context Learning with Large Language Models for Bundle Generationcited by 8
  24. 2024RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigmcited by 8
  25. 2024FineRec:Exploring Fine-grained Sequential Recommendationcited by 8
  26. 2024Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Modelscited by 6
  27. 2024The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendationcited by 4
  28. 2024Break the ID-Language Barrier: An Adaption Framework for LLM-based Sequential Recommendationcited by 3
  29. 2024SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systemscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 7.

9 papers.

  1. 2025ThinkRec: Thinking-based recommendation via LLMcited by 11
  2. 2025Mnemosyne: An Unsupervised, Human-Inspired Long-Term Memory Architecture for Edge-Based LLMscited by 2
  3. 2026From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agentscited by 2
  4. 2026RQ-GMM: Residual Quantized Gaussian Mixture Model for Multimodal Semantic Discretization in CTR Predictioncited by 1
  5. 2026Position: Recommender Systems Should Move Beyond Platform-Centric Ranking toward Personal Agent-Mediated Recommendationcited by 1
  6. 2026Distribution-Aware End-to-End Embedding for Streaming Numerical Features in Click-Through Rate Predictioncited by 0
  7. 2026Learning Evidence Highlighting for Frozen LLMscited by 0
  8. 2026RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendationcited by 0
  9. 2026RecPFN: Prior-Fitted Networks for In-Context-Based Recommendationscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Leveraging LLM Reasoning Enhances Personalized Recommender Systems
  2. 2024ReasoningRec: Bridging Personalized Recommendations and Human-Interpretable Explanations through LLM Reasoning
  3. 2025Towards Trustworthy LLM-Based Recommendation via Rationale Integration
  4. 2025MR.Rec: Synergizing Memory and Reasoning for Personalized Recommendation Assistant with LLMs
  5. 2025Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation
  6. 2025Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
  7. 2023How Can Recommender Systems Benefit from Large Language Models: A Survey
  8. 2024LANE: Logic Alignment of Non-tuning Large Language Models and Online Recommendation Systems for Explainable Reason Generation