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A list of awesome papers and resources of recommender system on large language model (LLM).
| Date | Stars |
|---|---|
| 2026-07-31 | 2301 |
| 2026-08-06 | 2302 |
Today
+1 stars today
This week
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This month
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# LLM for Recommendation Systems
A list of awesome papers and resources of recommender system on large language model (LLM).
🎉 ***News: Our LLM4Rec survey has been released.***
[A Survey on Large Language Models for Recommendation](https://arxiv.org/abs/2305.19860)
***The related work and projects will be updated soon and continuously.***
<div align="center">
<img src="https://github.com/WLiK/LLM4Rec-Awesome-Papers/blob/main/llm4rec_paradigms.png" alt="Editor" width="700">
</div>
If our work has been of assistance to you, please feel free to cite our survey. Thank you.
```
@article{llm4recsurvey,
author = {Likang Wu and Zhi Zheng and Zhaopeng Qiu and Hao Wang and Hongchao Gu and Tingjia Shen and Chuan Qin and Chen Zhu and Hengshu Zhu and Qi Liu and Hui Xiong and Enhong Chen},
title = {A Survey on Large Language Models for Recommendation},
journal = {CoRR},
volume = {abs/2305.19860},
year = {2023}
}
```
# Table of Contents
- [LLM for Recommendation Systems](#llm-for-recommendation-systems)
- [Table of Contents](#table-of-contents)
- [The papers and related projects](#the-papers-and-related-projects)
- [No Tuning](#no-tuning)
- [Supervised Fine-Tuning](#supervised-fine-tuning)
- [Related Survey](#related-survey)
- [Related Tutorial](#related-tutorial)
- [Common Datasets](#common-datasets)
- [Single card (RTX 3090) debuggable generative language models that support Chinese corpus](#single-card-rtx-3090-debuggable-generative-language-models-that-support-chinese-corpus)
## The papers and related projects
### No Tuning
Note: The tuning here only indicates whether the LLM model has been tuned.
| **Name** | **Paper** | **Venue** | **Year** | **Code** | LLM |
| -------- | ------------------------------------------------------------ | --------- | -------- | ------------------------------------------------------------ | --------------------- |
| N/A | [Large Language Models as Data Augmenters for Cold-Start Item Recommendation](https://arxiv.org/pdf/2402.11724.pdf) | arXiv | 2024 | N/A | PaLM |
| LLM4REC | [LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations](https://arxiv.org/pdf/2402.09617.pdf) | arXiv | 2024 | [Python](https://github.com/anord-wang/LLM4REC.git) | GPT2 |
| Lite-LLM4Rec | [Rethinking Large Language Model Architectures for Sequential Recommendations](https://arxiv.org/pdf/2402.09543.pdf) | arXiv | 2024 | N/A | T5 |
| Rec-GPT4V | [Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models](https://arxiv.org/pdf/2402.08670.pdf) | arXiv | 2024 | N/A | GPT4-V, LLaVA2 |
| LLM4Vis | [LLM4Vis: Explainable Visualization Recommendation using ChatGPT](https://arxiv.org/abs/2310.07652) | EMNLP | 2023 | [Python](https://github.com/demoleiwang/LLM4Vis) | GPT |
| LLMRec | [LLMRec: Large Language Models with Graph Augmentation for Recommendation](https://arxiv.org/abs/2311.00423) | WSDM | 2024 | [Python](https://github.com/HKUDS/LLMRec) | GPT |
|RLMRec | [Representation Learning with Large Language Models for Recommendation](https://arxiv.org/abs/2310.15950) | WWW | 2024 | [Python](https://github.com/HKUDS/RLMRec) | GPT-3.5 |
|KP4SR | [Knowledge Prompt-tuning for Sequential Recommendation](https://dl.acm.org/doi/abs/10.1145/3581783.3612252) | ACM | 2023 | N/A | GPT-3.5 |
|RecInterpreter | [Large Language Model Can Interpret Latent Space of Sequential Recommender](https://arxiv.org/abs/2310.20487) | arXiv | 2023 | [Python](https://github.com/YangZhengyi98/RecInterpreter) | LLaMA-7b |
| N/A | [Large Language Models as Zero-Shot Conversational Recommenders](https://arxiv.org/abs/2308.10053) | CIKM | 2023 | [Python](https://github.com/aaronheee/llms-as-zero-shot-conversational-recsys) | GPT-3.5-turbo ,GPT-4,BAIZE,Vicuna |
| Agent4Rec | [On Generative Agents in Recommendation](Excerpt of 27,562 characters
Read on GitHub
39
13
8
4
4
2
Cheng Yu · CS PhD student @ Westlake. BS @ USTC.
1
Zhmin Zhao · Software Analysis and Intelligence Lab (SAIL) & Lab on Maintenance, Construction and Intelligence of Software (MCIS) · Canada
1
Jinheon Baek
1
1
1
Xubin Ren · The University of Hong Kong
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4e63546881c626c1, topic:awesome, desc:a list of
matched fp:4e63546881c626c1, topic:large-language-models
matched fp:4e63546881c626c1, topic:datasets