Ruyu-Li / LLM4Rec

The repo of Large Lanuage Model (LLM) for recommendation system.

LLM for Recommendation Systems

An index of large language model (LLM) for recommendation systems.

🎉 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.

Table of Contents

• The papers and related projects
  • No Tuning
  • Supervised Fine-Tuning
  • Related Survey
• 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
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
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
RecLLM	Friedman, L., Ahuja, S., Allen, D., Tan, T., Sidahmed, H., Long, C., ... & Tiwari, M. (2023). Leveraging Large Language Models in Conversational Recommender Systems. arXiv preprint arXiv:2305.07961.	arxiv	2023	N/A	LaMDA(video)
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.	arxiv	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
DPLLM	Carranza, A. G., Farahani, R., Ponomareva, N., Kurakin, A., Jagielski, M., & Nasr, M. (2023). Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models. arXiv preprint arXiv:2305.05973.	arxiv	2023	N/A	T5
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
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

Supervised Fine-Tuning

Name	Paper	Venue	Year	Code	LLM
CTRL	[Li X, Chen B, Hou L, et al. CTRL: Connect Tabular and Language Model for CTR Prediction[J]. arXiv preprint arXiv:2306.02841, 2023.](Li X, Chen B, Hou L, et al. CTRL: Connect Tabular and Language Model for CTR Prediction[J]. arXiv preprint arXiv:2306.02841, 2023.)	arxiv	2023	N/A	P5(T5-based)
N/A	Li, R., Deng, W., Cheng, Y., Yuan, Z., Zhang, J., & Yuan, F. (2023). Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights. arXiv preprint arXiv:2305.11700.	arxiv	2023	N/A	OPT
PALR	Chen, Z. (2023). PALR: Personalization Aware LLMs for Recommendation. arXiv preprint arXiv:2305.07622.	arxiv	2023	N/A	LLaMa
InstructRec	Zhang, J., Xie, R., Hou, Y., Zhao, W. X., Lin, L., & Wen, J. R. (2023). Recommendation as instruction following: A large language model empowered recommendation approach. arXiv preprint arXiv:2305.07001.	arxiv	2023	N/A	FLAN-T5-3B
N/A	Kang, W. C., Ni, J., Mehta, N., Sathiamoorthy, M., Hong, L., Chi, E., & Cheng, D. Z. (2023). Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. arXiv preprint arXiv:2305.06474.	arxiv	2023	N/A	FLAN/ChatGPT
TALLRec	Bao, K., Zhang, J., Zhang, Y., Wang, W., Feng, F., & He, X. (2023). TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. arXiv preprint arXiv:2305.00447.	arxiv	2023	Python	Llama-7B
GPT4Rec	Li, J., Zhang, W., Wang, T., Xiong, G., Lu, A., & Medioni, G. (2023). GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation. arXiv preprint arXiv:2304.03879.	arxiv	2023	N/A	GPT-2
M6-Rec	Cui, Z., Ma, J., Zhou, C., Zhou, J., & Yang, H. (2022). M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems. arXiv preprint arXiv:2205.08084.	arxiv	2022	N/A	M6
N/A	Shen, T., Li, J., Bouadjenek, M. R., Mai, Z., & Sanner, S. (2023). Towards understanding and mitigating unintended biases in language model-driven conversational recommendation. Information Processing & Management, 60(1), 103139.	Inf Process Manag	2023	Python	BERT
P5	Geng, S., Liu, S., Fu, Z., Ge, Y., & Zhang, Y. (2022, September). Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5). In Proceedings of the 16th ACM Conference on Recommender Systems (pp. 299-315).	RecSys	2022	Python	T5
PEPLER	Li, L., Zhang, Y., & Chen, L. (2023). Personalized prompt learning for explainable recommendation. ACM Transactions on Information Systems, 41(4), 1-26.	TOIS	2023	Python	GPT-2
N/A	Zhang, Y., Ding, H., Shui, Z., Ma, Y., Zou, J., Deoras, A., & Wang, H. (2021). Language models as recommender systems: Evaluations and limitations.	NeurIPS workshop	2021	N/A	BERT/GPT-2

Related Survey

Paper	Venue	Year
Liu, P., Zhang, L., & Gulla, J. A. (2023). Pre-train, prompt and recommendation: A comprehensive survey of language modelling paradigm adaptations in recommender systems. arXiv preprint arXiv:2302.03735.	arxiv	2023

Single card (RTX 3090) debuggable generative language models that support Chinese corpus

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

Project	Year
baichuan-7B	2023
YuLan-chat	2023
Chinese-LLaMA-Alpaca	2023
THUDM/ChatGLM-6B	2023
FreedomIntelligence/LLMZoo Phoenix	2023
bloomz-7b1	2023
LianjiaTech/BELLE	2023

Hope our conclusion can help your work.