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Large Language Model-enhanced Recommender System Papers
| Date | Stars |
|---|---|
| 2026-07-31 | 764 |
| 2026-08-06 | 764 |
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<div align="center">
<h1>Awesome LLM4RS Papers</h1>
<a href="https://awesome.re">
<img src="https://awesome.re/badge.svg"/>
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This is a paper list about Large Language Model-enhanced Recommender System. It also contains some related works.
**Keywords**: *recommendation system, large language models*
Welcome to open an issue or make a pull request!
## Survey
+ Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review, arxiv 2024, [[paper]](https://arxiv.org/pdf/2402.18590).
+ A Survey on Large Language Models for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.19860).
+ How Can Recommender Systems Benefit from Large Language Models: A Survey, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.05817).
+ Recommender Systems in the Era of Large Language Models (LLMs), arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.02046).
+ A review of large language models and the recommendation task, Discover Artificial Intelligence (2025), [[paper]](https://link.springer.com/article/10.1007/s44163-025-00334-5).
## Paper List
+ Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System, arxiv 2023, [[paper]](https://arxiv.org/pdf/2303.14524).
+ GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.03879).
+ TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation, RecSys 2023 Short Paper, [[paper]](https://arxiv.org/pdf/2305.00447), [[code]](https://github.com/SAI990323/TALLRec).
+ Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.05973).
+ Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07001).
+ A First Look at LLM-Powered Generative News Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.06566).
+ Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.04518).
+ Zero-Shot Next-Item Recommendation using Large Pretrained Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.03153), [[code]](https://github.com/AGI-Edgerunners/LLM-Next-Item-Rec).
+ Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.06474).
+ Large Language Models are Zero-Shot Rankers for Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.08845), [[code]](https://github.com/RUCAIBox/LLMRank).
+ Leveraging Large Language Models in Conversational Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07961).
+ Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.13112), [[code]](https://github.com/RUCAIBox/iEvaLM-CRS).
+ PALR: Personalization Aware LLMs for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07622).
+ Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.01475).
+ A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.10702).
+ Large Language Model for Generative Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.00457).
+ GenRec: Large Language Model for Generative Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.00457).
+ Generative Job Recommendations with Large Language Model, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.02157).
+ LLM-Rec: Personalized Recommendation via Prompting Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.15780).
+ A Bi-Step GroundingExcerpt of 30,211 characters
Read on GitHub
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Xubin Ren · The University of Hong Kong
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Yupeng Hou · Google DeepMind
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Zhmin Zhao · Software Analysis and Intelligence Lab (SAIL) & Lab on Maintenance, Construction and Intelligence of Software (MCIS) · Canada
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Cheng Yu · CS PhD student @ Westlake. BS @ USTC.
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b8455fe606e51113, topic:large-language-models, topic:llm, topic:gpt
matched fp:b8455fe606e51113, topic:awesome-list, topic:papers