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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

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

Editor

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

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

Related Tutorial

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.


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