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Leveraging Large Language Models for Sequential Recommendation

arXiv 2309.09261 ↗First posted 17 Sep 2023cs.IRcited by 78

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Abstract (arXiv)

Sequential recommendation problems have received increasing attention in research during the past few years, leading to the inception of a large variety of algorithmic approaches. In this work, we explore how large language models (LLMs), which are nowadays introducing disruptive effects in many AI-based applications, can be used to build or improve sequential recommendation approaches. Specifically, we devise and evaluate three approaches to leverage the power of LLMs in different ways. Our results from experiments on two datasets show that initializing the state-of-the-art sequential recommendation model BERT4Rec with embeddings obtained from an LLM improves NDCG by 15-20% compared to the vanilla BERT4Rec model. Furthermore, we find that a simple approach that leverages LLM embeddings for producing recommendations, can provide competitive performance by highlighting semantically related items. We publicly share the code and data of our experiments to ensure reproducibility.

Key facts. Cited by 78 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2023.

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Citing papers per year: 2023: 3; 2024: 28; 2025: 35; 2026: 12.

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  1. 2024UrbanGPT: Spatio-Temporal Large Language Modelscited by 81
  2. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  3. 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendationcited by 47
  4. 2024CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendationcited by 44
  5. 2024Large Language Models for Next Point-of-Interest Recommendationcited by 40
  6. 2023Large Language Models for Intent-Driven Session Recommendationscited by 30
  7. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  8. 2025Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directionscited by 23
  9. 2025AgentCF++: Memory-enhanced LLM-based Agents for Popularity-aware Cross-domain Recommendationscited by 23
  10. 2024LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Applicationcited by 21
  11. 2024RDRec: Rationale Distillation for LLM-based Recommendationcited by 21
  12. 2024Language Representations Can be What Recommenders Need: Findings and Potentialscited by 18
38 more
  1. 2024Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendationcited by 17
  2. 2024Image Fusion for Cross-Domain Sequential Recommendationcited by 17
  3. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  4. 2024Federated Recommendation via Hybrid Retrieval Augmented Generationcited by 16
  5. 2025TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendationcited by 13
  6. 2025Towards User-level Private Reinforcement Learning with Human Feedbackcited by 13
  7. 2025Uncertainty Quantification and Decomposition for LLM-based Recommendationcited by 12
  8. 2025Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenderscited by 12
  9. 2023FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Predictioncited by 11
  10. 2024Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Modelcited by 11
  11. 2025LettinGo: Explore User Profile Generation for Recommendation Systemcited by 11
  12. 2024Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendationcited by 10
  13. 2024LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendationcited by 10
  14. 2024End-to-end Training for Recommendation with Language-based User Profilescited by 10
  15. 2025The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exitcited by 10
  16. 2024Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendationscited by 9
  17. 2025Improving LLM-powered Recommendations with Personalized Informationcited by 9
  18. 2023Adaptive In-Context Learning with Large Language Models for Bundle Generationcited by 8
  19. 2024Enhancing High-order Interaction Awareness in LLM-based Recommender Modelcited by 8
  20. 2024Preference Diffusion for Recommendationcited by 8
  21. 2024STAR: A Simple Training-free Approach for Recommendations using Large Language Modelscited by 8
  22. 2025Lost in Sequence: Do Large Language Models Understand Sequential Recommendation?cited by 8
  23. 2025Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Modelscited by 7
  24. 2025LLM-RecG: A Semantic Bias-Aware Framework for Zero-Shot Sequential Recommendationcited by 6
  25. 2025IGD: Token Decisiveness Modeling via Information Gain in LLMs for Personalized Recommendationcited by 5
  26. 2024The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trendscited by 4
  27. 2024The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendationcited by 4
  28. 2024FLARE: Fusing Language Models and Collaborative Architectures for Recommender Enhancementcited by 4
  29. 2025Pre-training Generative Recommender with Multi-Identifier Item Tokenizationcited by 4
  30. 2025Bidirectional Knowledge Distillation for Enhancing Sequential Recommendation with Large Language Modelscited by 4
  31. 2024Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendationcited by 3
  32. 2024DELRec: Distilling Sequential Pattern to Enhance LLMs-based Sequential Recommendationcited by 3
  33. 2025CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systemscited by 3
  34. 2024Privacy in LLM-based Recommendation: Recent Advances and Future Directionscited by 2
  35. 2025REGEN: A Dataset and Benchmarks with Natural Language Critiques and Narrativescited by 2
  36. 2025Listwise Preference Alignment Optimization for Tail Item Recommendationcited by 2
  37. 2025Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Searchcited by 2
  38. 2025Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendationcited by 2

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