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

The related work and projects will be updated soon and continuously.

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}
}

• The papers and related projects
  • No Tuning
  • Supervised Fine-Tuning
  • Related Survey
  • Common Datasets
• Single card (RTX 3090) debuggable generative language models that support Chinese corpus

Note: The tuning here only indicates whether the LLM model has been tuned.

Name	Paper	Venue	Year	Code	LLM
LLMRec	Wei, W., Ren, X., Tang, J., Wang, Q., Su, L., Cheng, S., Wang, J., Yin, D., & Huang, C. (2023). LLMRec: Large Language Models with Graph Augmentation for Recommendation. ArXiv Preprint ArXiv:2311.00423.	WSDM	2023	N/A	GPT
RLMRec	Ren, X., Wei, W., Xia, L., Su, L., Cheng, S., Wang, J., ... & Huang, C. (2023). Representation Learning with Large Language Models for Recommendation. arXiv preprint arXiv:2310.15950.	arXiv	2023	Python	GPT-3.5
KP4SR	Zhai, J., Zheng, X., Wang, C.-D., Li, H., & Tian, Y. (2023). Knowledge Prompt-tuning for Sequential Recommendation. Proceedings of the 31st ACM International Conference on Multimedia, 6451–6461.	ACM	2023	N/A	GPT-3.5
RecInterpreter	Large Language Model Can Interpret Latent Space of Sequential Recommender, Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He	arXiv	2023	Python	LLaMA-7b
N/A	Large Language Models as Zero-Shot Conversational Recommenders, Zhankui He*, Zhouhang Xie*, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Majumder, Nathan Kallus, Julian McAuley, Conference on Information and Knowledge Management, CIKM'23	CIKM	2023	Python	GPT-3.5-turbo ,GPT-4,BAIZE,Vicuna
Agent4Rec	Zhang A, Sheng L, Chen Y, et al. On Generative Agents in Recommendation[J]. arXiv preprint arXiv:2310.10108, 2023.	arxiv	2023	Python	GPT4
N/A	Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging	arxiv	2023	N/A	BLIP-2+GPT4
InteRecAgent	Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations	arxiv	2023	N/A	GPT4
GPT4SM	Peng, Wenjun, et al. "Are GPT Embeddings Useful for Ads and Recommendation?." International Conference on Knowledge Science, Engineering and Management. Cham: Springer Nature Switzerland, 2023.	KSEM	2023	Python	GPT
LLMRG	Wang, Y., Chu, Z., Ouyang, X., Wang, S., Hao, H., Shen, Y., ... & Li, S. (2023). Enhancing Recommender Systems with Large Language Model Reasoning Graphs. arXiv preprint arXiv:2308.10835.	arxiv	2023	N/A	GPT-3.5/GPT4
RAH	Shu, Y., Gu, H., Zhang, P., Zhang, H., Lu, T., Li, D., & Gu, N. (2023). RAH! RecSys-Assistant-Human: A Human-Central Recommendation Framework with Large Language Models. arXiv preprint arXiv:2308.09904.	arxiv	2023	N/A	GPT4
LLM-Rec	Lyu, Hanjia, et al. "LLM-Rec: Personalized Recommendation via Prompting Large Language Models." arXiv preprint arXiv:2307.15780 (2023).	arxiv	2023	N/A	GPT-3
N/A	Sanner, S., Balog, K., Radlinski, F., Wedin, B., & Dixon, L. (2023). Large Language Models are Competitive Near Cold-start Recommenders for Language-and Item-based Preferences. arXiv preprint arXiv:2307.14225.	RecSys	2023	N/A	PaLM
MINT	Mysore S, McCallum A, Zamani H. Large Language Model Augmented Narrative Driven Recommendations[J]. arXiv preprint arXiv:2306.02250, 2023.	Recsys	2023	N/A	175B InstructGPT
KAR	Xi, Y., Liu, W., Lin, J., Zhu, J., Chen, B., Tang, R., ... & Yu, Y. (2023). Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. arXiv preprint arXiv:2306.10933.	arxiv	2023	Python	ChatGLM
RecAgent	Wang, L., Zhang, J., Chen, X., Lin, Y., Song, R., Zhao, W. X., & Wen, J. R. (2023). RecAgent: A Novel Simulation Paradigm for Recommender Systems. arXiv preprint arXiv:2306.02552.	arxiv	2023	Python	ChatGPT
AnyPredict	Wang Z, Gao C, Xiao C, et al. AnyPredict: Foundation Model for Tabular Prediction[J]. arXiv preprint arXiv:2305.12081, 2023.	arxiv	2023	N/A	ChatGPT,BioBERT
iEvaLM	Wang, X., Tang, X., Zhao, W. X., Wang, J., & Wen, J. R. (2023). Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models. arXiv preprint arXiv:2305.13112.	arxiv	2023	Python	ChatGPT
N/A	Hou, Y., Zhang, J., Lin, Z., Lu, H., Xie, R., McAuley, J., & Zhao, W. X. (2023). Large Language Models are Zero-Shot Rankers for Recommender Systems. arXiv preprint arXiv:2305.08845.	arxiv	2023	Python	ChatGPT
FaiRLLM	Zhang, J., Bao, K., Zhang, Y., Wang, W., Feng, F., & He, X. (2023). Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. arXiv preprint arXiv:2305.07609.	Recsys	2023	Python	ChatGPT
GENRE	Liu, Q., Chen, N., Sakai, T., & Wu, X. M. (2023). A First Look at LLM-Powered Generative News Recommendation. arXiv preprint arXiv:2305.06566.	arxiv	2023	Python	ChatGPT
N/A	Lin, G., & Zhang, Y. (2023). Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT. arXiv preprint arXiv:2305.04518.	arxiv	2023	N/A	ChatGPT
N/A	Dai, S., Shao, N., Zhao, H., Yu, W., Si, Z., Xu, C., ... & Xu, J. (2023). Uncovering ChatGPT's Capabilities in Recommender Systems. arXiv preprint arXiv:2305.02182.	arxiv	2023	Python	ChatGPT
N/A	Liu, J., Liu, C., Lv, R., Zhou, K., & Zhang, Y. (2023). Is ChatGPT a Good Recommender? A Preliminary Study. arXiv preprint arXiv:2304.10149.	arxiv	2023	N/A	ChatGPT
VQ-Rec	Hou Y, He Z, McAuley J, et al. Learning vector-quantized item representation for transferable sequential recommenders[C]//Proceedings of the ACM Web Conference 2023. 2023: 1162-1171.	ACM	2023	Python	BERT
RankGPT	Sun, W., Yan, L., Ma, X., Ren, P., Yin, D., & Ren, Z. (2023). Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent. arXiv preprint arXiv:2304.09542.	arxiv	2023	Python	ChatGPT/4
GeneRec	Wang, W., Lin, X., Feng, F., He, X., & Chua, T. S. (2023). Generative Recommendation: Towards Next-generation Recommender Paradigm. arXiv preprint arXiv:2304.03516.	arxiv	2023	Python	N/A
NIR	Wang, L., & Lim, E. P. (2023). Zero-Shot Next-Item Recommendation using Large Pretrained Language Models. arXiv preprint arXiv:2304.03153.	arxiv	2023	Python	GPT-3.5
Chat-REC	Gao, Y., Sheng, T., Xiang, Y., Xiong, Y., Wang, H., & Zhang, J. (2023). Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System. arXiv preprint arXiv:2303.14524.	arxiv	2023	N/A	ChatGPT
N/A	Sileo, D., Vossen, W., & Raymaekers, R. (2022, April). Zero-Shot Recommendation as Language Modeling. In Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022..	ECIR	2022	Python	GPT-2
UniCRS	Wang, X., Zhou, K., Wen, J. R., & Zhao, W. X. (2022, August). Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 1929-1937).	KDD	2022	Python	GPT-2/ DialoGPT /BART
LLMRec	Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang. arXiv preprint arXiv:2311.00423, 2023.	WSDM	2024	Python	ChatGPT
K-LaMP	Jinheon Baek, Nirupama Chandrasekaran, Silviu Cucerzan, Allen herring, Sujay Kumar Jauhar. arXiv preprint arXiv:2311.06318, 2023.	arXiv	2023	N/A	GPT-4

Some open-source and effective projects can be adpated to the recommendation systems based on Chinese textual data. Especially for the individual researchers !

Hope our conclusion can help your work.