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

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}
}

LLM for Recommendation Systems
Table of Contents
- The papers and related projects

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	arXiv	2024	N/A	PaLM
LLM4REC	LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations	arXiv	2024	Python	GPT2
Lite-LLM4Rec	Rethinking Large Language Model Architectures for Sequential Recommendations	arXiv	2024	N/A	T5
Rec-GPT4V	Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models	arXiv	2024	N/A	GPT4-V, LLaVA2
LLM4Vis	LLM4Vis: Explainable Visualization Recommendation using ChatGPT	EMNLP	2023	Python	GPT
LLMRec	LLMRec: Large Language Models with Graph Augmentation for Recommendation	WSDM	2024	Python	GPT
RLMRec	Representation Learning with Large Language Models for Recommendation	WWW	2024	Python	GPT-3.5
KP4SR	Knowledge Prompt-tuning for Sequential Recommendation	ACM	2023	N/A	GPT-3.5
RecInterpreter	Large Language Model Can Interpret Latent Space of Sequential Recommender	arXiv	2023	Python	LLaMA-7b
N/A	Large Language Models as Zero-Shot Conversational Recommenders	CIKM	2023	Python	GPT-3.5-turbo ,GPT-4,BAIZE,Vicuna
Agent4Rec	On Generative Agents in Recommendation	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	Are GPT Embeddings Useful for Ads and Recommendation?	KSEM	2023	Python	GPT
LLMRG	Enhancing Recommender Systems with Large Language Model Reasoning Graphs	arxiv	2023	N/A	GPT-3.5/GPT4
RAH	RAH! RecSys-Assistant-Human: A Human-Central Recommendation Framework with Large Language Models	arxiv	2023	N/A	GPT4
LLM-Rec	LLM-Rec: Personalized Recommendation via Prompting Large Language Models	arxiv	2023	N/A	GPT-3
N/A	Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata	RecSys	2023	N/A	GPT4
N/A	Retrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language Models	RecSys	2023	N/A	ChatGPT
N/A	LLM Based Generation of Item-Description for Recommendation System	RecSys	2023	N/A	Alpaca
N/A	Large Language Models are Competitive Near Cold-start Recommenders for Language-and Item-based Preferences	RecSys	2023	N/A	PaLM
MINT	Large Language Model Augmented Narrative Driven Recommendations	Recsys	2023	N/A	175B InstructGPT
KAR	Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models	arxiv	2023	Python	ChatGLM
RecAgent	RecAgent: A Novel Simulation Paradigm for Recommender Systems	arxiv	2023	Python	ChatGPT
AnyPredict	AnyPredict: Foundation Model for Tabular Prediction	arxiv	2023	N/A	ChatGPT,BioBERT
iEvaLM	Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models	arxiv	2023	Python	ChatGPT
N/A	Large Language Models are Zero-Shot Rankers for Recommender Systems	arxiv	2023	Python	ChatGPT
FaiRLLM	Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation	Recsys	2023	Python	ChatGPT
GENRE	A First Look at LLM-Powered Generative News Recommendation	arxiv	2023	Python	ChatGPT
N/A	Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT	arxiv	2023	N/A	ChatGPT
N/A	Uncovering ChatGPT's Capabilities in Recommender Systems	arxiv	2023	Python	ChatGPT
N/A	Is ChatGPT a Good Recommender? A Preliminary Study	arxiv	2023	N/A	ChatGPT
VQ-Rec	Learning vector-quantized item representation for transferable sequential recommenders	ACM	2023	Python	BERT
RankGPT	Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent	arxiv	2023	Python	ChatGPT/4
GeneRec	Generative Recommendation: Towards Next-generation Recommender Paradigm	arxiv	2023	Python	N/A
NIR	Zero-Shot Next-Item Recommendation using Large Pretrained Language Models	arxiv	2023	Python	GPT-3.5
Chat-REC	Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System	arxiv	2023	N/A	ChatGPT
N/A	Zero-Shot Recommendation as Language Modeling	ECIR	2022	Python	GPT-2
UniCRS	Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning	KDD	2022	Python	GPT-2/ DialoGPT /BART
LLMRec	LLMRec: Large Language Models with Graph Augmentation for Recommendation	WSDM	2024	Python	ChatGPT
K-LaMP	K-LaMP: Knowledge-Guided Language Model Pre-training for Sequential Recommendation	arXiv	2023	N/A	GPT-4

Supervised Fine-Tuning

Name	Paper	Venue	Year	Code	LLM
N/A	Aligning Large Language Models for Controllable Recommendations	arXiv	2024	N/A	llama2
SLIM	Can Small Language Models be Good Reasoners for Sequential Recommendation?	arXiv	2024	N/A	ChatGPT,llama2
GPT-FedRec	Federated Recommendation via Hybrid Retrieval Augmented Generation	arXiv	2024	N/A	E5
NoteLLM	NoteLLM: A Retrievable Large Language Model for Note Recommendation	WWW	2024	N/A	llama2
N/A	Enhancing Recommendation Diversity by Re-ranking with Large Language Models	arXiv	2024	N/A	ChatGPT, LLaMA2
LLama4Rec	Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation	arXiv	2024	N/A	LLaMA
N/A	Large Language Model with Graph Convolution for Recommendation	arXiv	2024	N/A	GPT4,LLaMA2,ChatGLM
LLM-InS	Large Language Model Interaction Simulator for Cold-Start Item Recommendation	arXiv	2024	N/A	LLaMA2
LLM4REC	LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations	arXiv	2024	Python	GPT2
Fed4Rec	LLM-based Federated Recommendation	arXiv	2024	N/A	LLaMA
SPAR	SPAR: Personalized Content-Based Recommendation via Long Engagement Attention	arXiv	2024	N/A	BERT
LLaRA	LLaRA: Aligning Large Language Models with Sequential Recommenders	arxiv	2023	Python	Llama-2
E4SRec	E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation	arxiv	2023	Python	Llama-2
LlamaRec	LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking	arxiv	2023	Python	Llama-2
CLLM4Rec	Collaborative Large Language Model for Recommender Systems	arxiv	2023	Python	GPT2
TransRec	A Multi-facet Paradigm to Bridge Large Language Model and Recommendation	arxiv	2023	N/A	BART-large and LLaMA-7B
RecMind	RecMind: Large Language Model Powered Agent For Recommendation	arXiv	2023	N/A	ChatGPT,P5
RecSysLLM	Leveraging Large Language Models for Pre-trained Recommender Systems	arxiv	2023	N/A	GLM-10B
N/A	Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM	RecSys	2023	N/A	ChatGLM-6B,P5
N/A	Prompt Distillation for Efficient LLM-based Recommendation	RecSys	2023	N/A	T5,P5
BIGRec	A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems	arxiv	2023	Python	LLaMA
LLMCRS	A Large Language Model Enhanced Conversational Recommender System	arxiv	2023	N/A	Flan-T5/LLaMA
GLRec	Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations	arxiv	2023	Python	BELLE
GIRL	Generative Job Recommendations with Large Language Model	arxiv	2023	N/A	BELLE
Amazon-M2	Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation	arxiv	2023	Project	mT5
GenRec	GenRec: Large Language Model for Generative Recommendation	arxiv	2023	Python	LLaMA
RecLLM	Leveraging Large Language Models in Conversational Recommender Systems	arxiv	2023	N/A	LaMDA(video)
ONCE	ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models	arXiv	2023	Python	ChatGPT,Llama
DPLLM	Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models	arxiv	2023	N/A	T5
PBNR	PBNR: Prompt-based News Recommender System	arxiv	2023	N/A	T5
GPTRec	Generative Sequential Recommendation with GPTRec	Gen-IR@SIGIR	2023	N/A	GPT-2
CTRL	CTRL: Connect Tabular and Language Model for CTR Prediction	arxiv	2023	N/A	RoBERTa/GLM
UniTRec	UniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based Recommendation	ACL	2023	Python	BART
ICPC	Large Language Models for User Interest Journeys	arxiv	2023	N/A	LaMDA
TransRec	Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights	arxiv	2023	N/A	RoBERTa
N/A	Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights	arxiv	2023	N/A	OPT
PALR	PALR: Personalization Aware LLMs for Recommendation	arxiv	2023	N/A	LLaMa
InstructRec	Recommendation as instruction following: A large language model empowered recommendation approach	arxiv	2023	N/A	FLAN-T5-3B
N/A	Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction	arxiv	2023	N/A	FLAN/ChatGPT
LSH	Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study	arxiv	2023	N/A	BERT
TALLRec	TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation	arxiv	2023	Python	Llama-7B
GPT4Rec	GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation	arxiv	2023	N/A	GPT-2
IDvs.MoRec	Where to go next for recommender systems? id-vs. modality-based recommender models revisited	SIGIR	2023	Python	BERT
GReaT	Language models are realistic tabular data generators	ICLR	2023	Python	GPT-2
M6-Rec	M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems	arxiv	2022	N/A	M6
N/A	Towards understanding and mitigating unintended biases in language model-driven conversational recommendation	Inf Process Manag	2023	Python	BERT
P5	Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5)	RecSys	2022	Python	T5
PEPLER	Personalized prompt learning for explainable recommendation	TOIS	2023	Python	GPT-2
N/A	Language models as recommender systems: Evaluations and limitations	NeurIPS workshop	2021	N/A	BERT/GPT-2

Related Survey

Paper	Venue	Year
Large Language Models for Generative Recommendation: A Survey and Visionary Discussions	arxiv	2023
Robust Recommender System: A Survey and Future Directions	arxiv	2023
A Survey on Multi-Behavior Sequential Recommendation	arxiv	2023
When large language models meet personalization: Perspectives of challenges and opportunities	arxiv	2023
Recommender systems in the era of large language models (llms)	arxiv	2023
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News	arxiv	2023
How Can Recommender Systems Benefit from Large Language Models: A Survey	arxiv	2023
Pre-train, prompt and recommendation: A comprehensive survey of language modelling paradigm adaptations in recommender systems	arxiv	2023

Name	Venue	Year
Large Language Models for Recommendation: Progresses and Future Directions	SIGIR-AP	2023
Tutorial on Large Language Models for Recommendation	RecSys	2023

Common Datasets

Name	Scene	Tasks	Information	URL
Amazon Review	Commerce	Seq Rec/CF Rec	This is a large crawl of product reviews from Amazon. Ratings: 82.83 million, Users: 20.98 million, Items: 9.35 million, Timespan: May 1996 - July 2014	link
Amazon-M2	Commerce	Seq Rec/CF Rec	A large dataset of anonymized user sessions with their interacted products collected from multiple language sources at Amazon. It includes 3,606,249 train sessions, 361,659 test sessions, and 1,410,675 products.	link
Steam	Game	Seq Rec/CF Rec	Reviews represent a great opportunity to break down the satisfaction and dissatisfaction factors around games. Reviews: 7,793,069, Users: 2,567,538, Items: 15,474, Bundles: 615	link
MovieLens	Movie	General	The dataset consists of 4 sub-datasets, which describe users' ratings to movies and free-text tagging activities from MovieLens, a movie recommendation service.	link
Yelp	Commerce	General	There are 6,990,280 reviews, 150,346 businesses, 200,100 pictures, 11 metropolitan areas, 908,915 tips by 1,987,897 users. Over 1.2 million business attributes like hours, parking, availability, etc.	link
Douban	Movie, Music, Book	Seq Rec/CF Rec	This dataset includes three domains, i.e., movie, music, and book, and different kinds of raw information, i.e., ratings, reviews, item details, user profiles, tags (labels), and date.	link
MIND	News	General	MIND contains about 160k English news articles and more than 15 million impression logs generated by 1 million users. Every news contains textual content including title, abstract, body, category, and entities.	link
U-NEED	Commerce	Conversation Rec	U-NEED consists of 7,698 fine-grained annotated pre-sales dialogues, 333,879 user behaviors, and 332,148 product knowledge tuples.	link
PixelRec	Short Video	Seq Rec/CF Rec	PixelRec is a large dataset of cover images collected from a short video recommender system, comprising approximately 200 million user image interactions, 30 million users, and 400,000 video cover images. The texts and other aggregated attributes of videos are also included.	link
KuaiSAR	Video	Search and Rec	KuaiSAR contains genuine search and recommendation behaviors of 25,877 users, 6,890,707 items, 453,667 queries, and 19,664,885 actions within a span of 19 days on the Kuaishou app	link
Tenrec	Video, Article	General	Tenrec is a large-scale benchmark dataset for recommendation systems. It contains around 5 million users and 140 million interactions.	link
NineRec	Video, Article	General	NineRec is a TransRec dataset suite that includes a large-scale source domain recommendation dataset and nine diverse target domain recommendation datasets. Each item in NineRec is represented by a text description and a high-resolution cover image.	link
MicroLens	Video	General	MicroLens is a very large micro-video recommendation dataset containing one billion user-item interactions, 34 million users, and one million micro-videos. It includes various modality information about videos and serves as a benchmark for content-driven micro-video recommendation research.	link

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

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

Project	Year
Qwen-7B	2023
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.

asfathermou/LLM4Rec-Awesome-Papers