Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/nancheng58/Awesome-LLM4RS-Papers

Large Language Model-enhanced Recommender System Papers
https://github.com/nancheng58/Awesome-LLM4RS-Papers

List: Awesome-LLM4RS-Papers

awesome-list gpt large-language-models llm papers pre-training prompt-tuning recommender-system survey

Last synced: 27 days ago
JSON representation

Large Language Model-enhanced Recommender System Papers

Awesome Lists containing this project

README 

        


    
Awesome LLM4RS Papers


    

        

    




This is a paper list about Large Language Model-enhanced Recommender System. It also contains some related works.



**Keywords**: *recommendation system, large language models*



Welcome to open an issue or make a pull request!



## Survey

+ Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review, arxiv 2024, [[paper]](https://arxiv.org/pdf/2402.18590).

+ A Survey on Large Language Models for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.19860).

+ How Can Recommender Systems Benefit from Large Language Models: A Survey, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.05817).

+ Recommender Systems in the Era of Large Language Models (LLMs), arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.02046).



## Paper List

+ Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System, arxiv 2023, [[paper]](https://arxiv.org/pdf/2303.14524).

+ GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.03879).

+ TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation, RecSys 2023 Short Paper, [[paper]](https://arxiv.org/pdf/2305.00447), [[code]](https://github.com/SAI990323/TALLRec).

+ Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.05973).

+ Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07001).

+ A First Look at LLM-Powered Generative News Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.06566).

+ Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.04518).

+ Zero-Shot Next-Item Recommendation using Large Pretrained Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.03153), [[code]](https://github.com/AGI-Edgerunners/LLM-Next-Item-Rec).

+ Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.06474).

+ Large Language Models are Zero-Shot Rankers for Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.08845), [[code]](https://github.com/RUCAIBox/LLMRank).

+ Leveraging Large Language Models in Conversational Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07961).

+ Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.13112), [[code]](https://github.com/RUCAIBox/iEvaLM-CRS).

+ PALR: Personalization Aware LLMs for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.07622).

+ Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.01475).

+ A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.10702).

+ Large Language Model for Generative Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.00457).

+ GenRec: Large Language Model for Generative Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.00457).

+ Generative Job Recommendations with Large Language Model, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.02157).

+ Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.05722).

+ LLM-Rec: Personalized Recommendation via Prompting Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2307.15780).

+ A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2308.08434).

+ LLMRec: Benchmarking Large Language Models on Recommendation Task, arxiv 2023, [[paper]](https://arxiv.org/pdf/2308.12241),[[code]](https://github.com/williamliujl/LLMRec).

+ Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging, arxiv 2023, [[paper]](https://arxiv.org/pdf/2309.01026).

+ Prompt Distillation for Efficient LLM-based Recommendation, CIKM 2023, [[paper]](https://lileipisces.github.io/files/CIKM23-POD-paper.pdf), [[code]](https://github.com/lileipisces/POD).

+ Large Language Models as Zero-Shot Conversational Recommenders, CIKM 2023, [[paper]](https://arxiv.org/pdf/2308.10053), [[code]](https://github.com/AaronHeee/LLMs-as-Zero-Shot-Conversational-RecSys).

+ Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2310.09874).

+ Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging, arxiv 2023, [[paper]](https://arxiv.org/pdf/2309.01026).

+ LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking, arxiv 2023, [[paper]](https://github.com/Yueeeeeeee/LlamaRec/blob/main/media/paper.pdf), [[code]](https://github.com/Yueeeeeeee/LlamaRec).

+ Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences, Recsys 2023, [[paper]](https://arxiv.org/pdf/2307.14225).

+ CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2310.19488).

+ Large Language Model Augmented Narrative Driven Recommendations, RecSys 2023 Short Paper, [[paper]](https://arxiv.org/pdf/2306.02250).

+ Leveraging Large Language Models for Sequential Recommendation, RecSys 2023 LBR, [[paper]](https://arxiv.org/pdf/2309.09261), [[code]](https://github.com/dh-r/LLM-Sequential-Recommendation).

+ ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models, WSDM 2024, [[paper]](https://arxiv.org/pdf/2305.06566), [[code]](https://github.com/Jyonn/ONCE).

+ LLaRA: Aligning Large Language Models with Sequential Recommenders, arxiv 2023, [[paper]](https://arxiv.org/pdf/2312.02445), [[code]](https://github.com/ljy0ustc/LLaRA).

+ LLM4Vis: Explainable Visualization Recommendation using ChatGPT, arxiv 2023, [[paper]](https://arxiv.org/pdf/2310.07652), [[code]](https://github.com/demoleiwang/LLM4Vis).

+ E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2312.02443), [[code]](https://github.com/HestiaSky/E4SRec/).

+ Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2311.09049), [[code]](https://github.com/RUCAIBox/LC-Rec/).

+ Representation Learning with Large Language Models for Recommendation, WWW 2024, [[paper]](https://arxiv.org/pdf/2310.15950), [[code]](https://github.com/HKUDS/RLMRec).

+ Stealthy Attack on Large Language Model based Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2402.14836).

+ ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2308.11131) [[code]](https://github.com/LaVieEnRose365/ReLLa)

+ Wukong: Towards a Scaling Law for Large-Scale Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2403.02545)

+ A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment Recommendation, arxiv 2024, [[paper]]((http://arxiv.org/pdf/2403.13574))[[code]](https://github.com/RUCAIBox/LSVCR/)

+ Harnessing Large Language Models for Text-Rich Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2403.13325)  

+ Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations, arxiv 2024, [[paper]](https://arxiv.org/pdf/2307.05722)[[code]](https://github.com/WLiK/GLRe)

+ LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs, arxiv 2024, [[paper]](https://arxiv.org/pdf/2308.10835)

+ Enhancing Job Recommendation through LLM-based Generative Adversarial Networks, AAAI 2024, [[paper]](https://arxiv.org/pdf/2307.10747).

+ LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2401.08217).

+ Sequential Recommendation with Latent Relations based on Large Language Model, SIGIR 2024, [[paper]](https://arxiv.org/pdf/2403.18348), [[code]](https://github.com/ysh-1998/lrd).

+ Common Sense Enhanced Knowledge-based Recommendation with Large Language Model, arxiv 2024, [[paper]](https://arxiv.org/pdf/2403.18325)[[code]](https://github.com/ysh-1998/csrec)

+ Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2403.16427)

+ Enhancing Content-based Recommendation via Large Language Model, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.00236)

+ Aligning Large Language Models with Recommendation Knowledge, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.00245)

+ Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.01855)

+ DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.06311).

+ Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommendation Systems, SIGIR 2024, [[paper]](http://arxiv.org/pdf/2404.11773), [[code]](https://github.com/dayuyang1999/Behavior-Alignment).

+ Exact and Efficient Unlearning for Large Language Model-based Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2404.10327).

+ Large Language Models for Intent-Driven Session Recommendations, SIGIR 24, [[paper]](https://arxiv.org/pdf/2312.07552).

+ Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling, SIGIR 24, [[paper]](https://arxiv.org/pdf/2403.16948).

+ Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning, SIGIR 24, [[paper]](https://arxiv.org/pdf/2403.00843).

+ LoRec: Large Language Model for Robust Sequential Recommendation against Poisoning Attacks, SIGIR 24, [[paper]](https://arxiv.org/pdf/2401.17723).

+ Data-efficient Fine-tuning for LLM-based Recommendation, SIGIR 24, [[paper]](https://arxiv.org/pdf/2401.17197).

+ Towards LLM-RecSys Alignment with Textual ID Learning , SIGIR 24, [[paper]](https://arxiv.org/pdf/2403.19021).

+ Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors, SIGIR 24, [[paper]](https://arxiv.org/pdf/2403.19347).

+  RecGPT: Generative Personalized Prompts for Sequential Recommendation  via ChatGPT Training Paradigm, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.08675)

+ Efficient and Responsible Adaptation of Large Language Models for Robust  Top-k Recommendations, arxiv 2024, [[paper]](https://arxiv.org/pdf/2405.00824).

+ Large Language Models for Next Point-of-Interest Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.17591).

+ Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model, arxiv 2024, [[paper]](https://arxiv.org/pdf/2405.00338).

+ Large Language Models as Conversational Movie Recommenders: A User Study, arxiv 2024, [[paper]](https://arxiv.org/pdf/2404.19093).

+ CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2405.02429).

+ Fine-Tuning Large Language Model Based Explainable Recommendation with Explainable Quality Reward,  AAAI 2024, [[paper]](https://ojs.aaai.org/index.php/AAAI/article/view/28777).

+ Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph, arxiv 2024, [[paper]](https://arxiv.org/pdf/2402.13750).

+ RDRec: Rationale Distillation for LLM-based Recommendation, ACL 2024 Main (short), [[paper]](https://arxiv.org/pdf/2405.10587), [[code]](https://github.com/WangXFng/RDRec).

+ Reinforced Prompt Personalization for Recommendation with Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.17115), [[code]](https://github.com/maowenyu-11/rpp)

+ Semantic Understanding and Data Imputation using Large Language Model to Accelerate Recommendation System, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.10078)

+ A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.04069)

+ LANE: Logic Alignment of Non-tuning Large Language Models and Online Recommendation Systems for Explainable Reason Generation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.02833)

+ Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.14169)

+ "You Gotta be a Doctor, Lin": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.12232)

+ Multi-Layer Ranking with Large Language Models for News Source Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.11745)

+ Large Language Models as Evaluators for Recommendation Explanations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.03248)

+ Text-like Encoding of Collaborative Information in Large Language Models for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.03210)

+ Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2406.03085)

+ XRec: Large Language Models for Explainable Recommendation, arxiv 2024, [[paper]](XRec: Large Language Models for Explainable Recommendation), [[code]](https://github.com/hkuds/xrec)

+ Large Language Models Enhanced Sequential Recommendation for Long-tail User and Item, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.20646), [[code]](https://github.com/liuqidong07/LLM-ESR)

+ Keyword-driven Retrieval-Augmented Large Language Models for Cold-start User Recommendations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.19612)

+ News Recommendation with Category Description by a Large Language Model, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.13007)

+ Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.12442)

+ Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.12119)

+ EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.11441)

+ DynLLM: When Large Language Models Meet Dynamic Graph Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.07580)

+ Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/pdf/2405.05060)

+ OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems, Sigir 2024, [[paper]](https://arxiv.org/pdf/2310.09233), [[code]](https://github.com/agiresearch/OpenP5)

+ LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding, [[paper]](http://arxiv.org/abs/2408.11523)

+ Large Language Model Driven Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.10946)

+ CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation, [[paper]](http://arxiv.org/abs/2408.10645)

+ Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.10520)

+ Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.09698)

+ Collaborative Cross-modal Fusion with Large Language Model for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.08564)

+ LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.08208)

+ Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.06276)

+ Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.03533)

+ Large Language Model Aided QoS Prediction for Service Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2408.02223)

+ Learn by Selling: Equipping Large Language Models with Product Knowledge for Context-Driven Recommendations, arxiv 2024, [[paper]](http://arxiv.org/abs/2407.20856)

+ Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2407.19643)

+ Reinforced Prompt Personalization for Recommendation with Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/abs/2407.17115)

+ LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding, [[paper]](http://arxiv.org/pdf/2408.11523)

+ Large Language Model Driven Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.10946)

+ CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation, [[paper]](http://arxiv.org/pdf/2408.10645)

+ Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.10520)

+ Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.09698)

+ Collaborative Cross-modal Fusion with Large Language Model for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.08564)

+ LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.08208)

+ Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.06276)

+ Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.03533)

+ Large Language Model Aided QoS Prediction for Service Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2408.02223)

+ Learn by Selling: Equipping Large Language Models with Product Knowledge for Context-Driven Recommendations, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.20856)

+ Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components Recommendation, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.19643)

+ Reinforced Prompt Personalization for Recommendation with Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/pdf/2407.17115)

+ Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System, KDD 2024, [[paper]](http://arxiv.org/pdf/2404.11343).

+ Item-Language Model for Conversational Recommendation, arxiv 2024, [[paper]](https://arxiv.org/pdf/2406.02844)

+ A-LLMRec: Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System, KDD 2024, [[paper]](https://arxiv.org/pdf/2406.02844), [[code]](https://github.com/ghdtjr/A-LLMRec)

+ HierLLM: Hierarchical Large Language Model for Question Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.06177)

+ User Preferences for Large Language Model versus Template-Based Explanations of Movie Recommendations: A Pilot Study, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.06297)

+ Large Language Model Enhanced Hard Sample Identification for Denoising Recommendation, [[paper]](http://arxiv.org/abs/2409.10343)

+ Semantics Preserving Emoji Recommendation with Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.10760)

+ HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.12740)

+ Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.15373)

+ A Prompting-Based Representation Learning Method for Recommendation with Large Language Models, arxiv 2024, [[paper]](http://arxiv.org/abs/2409.16674)

+ Large Language Model Empowered Embedding Generator for Sequential Recommendation, arxiv 2024, [paper](http://arxiv.org/abs/2409.19925), [[code]](https://github.com/liuqidong07/LLMEmb)

+ Cognitive Biases in Large Language Models for News Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2410.02897)

+ Efficient Inference for Large Language Model-based Generative Recommendation, arxiv 2024, [[paper]](http://arxiv.org/abs/2410.05165)

  

### Agent4Rec

+ When Large Language Model based Agent Meets User Behavior Analysis: A Novel User Simulation Paradigm, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.02552).

+ RecMind: Large Language Model Powered Agent For Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2308.14296).

+ On Generative Agents in Recommendation, arxiv 2023, [[paper]](https://arxiv.org/pdf/2310.10108), [[code]](https://github.com/LehengTHU/Agent4Rec).

+ AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2310.09233).

+ Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations [[link]](https://arxiv.org/pdf/2308.16505.pdf)

+ Balancing Information Perception with Yin-Yang: Agent-Based Information Neutrality Model for Recommendation Systems, arxiv 2024, [[paper]](http://arxiv.org/pdf/2404.04906)

+ Lending Interaction Wings to Recommender Systems with Conversational Agents, NeurIPS 2023, [[paper]](https://arxiv.org/pdf/2310.04230).

+ A Conceptual Framework for Conversational Search and Recommendation: Conceptualizing Agent-Human Interactions During the Conversational Search Process, arxiv 2024, [[paper]](http://arxiv.org/pdf/2404.08630).



### Knowledge Augmentation

+ Enhancing Recommender Systems with Large Language Model Reasoning Graphs, arxiv 2023, [[paper]](https://arxiv.org/pdf/2308.10835). 

+ Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models, arxiv 2023, [[paper]](https://arxiv.org/pdf/2306.10933), [[code]](https://github.com/YunjiaXi/Open-World-Knowledge-Augmented-Recommendation).

+ LLMRec: Large Language Models with Graph Augmentation for Recommendation, WSDM 2024, [[paper]](https://arxiv.org/pdf/2311.00423), [[code]](https://github.com/HKUDS/LLMRec), [[blog in Chinese]](https://mp.weixin.qq.com/s/aU-uzLWH6xfIuoon-Zq8Cg).

+ Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application, arxiv 2024, [[paper]](https://arxiv.org/pdf/2405.03988). 



### Perspective

+ Language models as recommender systems: Evaluations and limitations, NeurIPS Workshop 2021, [[paper]](https://openreview.net/forum?id=hFx3fY7-m9b).

+ Generative Recommendation: Towards Next-generation Recommender Paradigm, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.03516).

+ Where to Go Next for Recommender Systems? ID- vs.Modality-based recommender models revisited, SIGIR 2023, [[paper]](https://arxiv.org/pdf/2303.13835.pdf), [[code]](https://github.com/westlake-repl/IDvs.MoRec)

+ Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.11700.pdf).

+ Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights, arxiv 2023, [[paper]](https://arxiv.org/pdf/2305.15036).

+ Is ChatGPT a Good Recommender? A Preliminary Study, arxiv 2023, [[paper]](https://arxiv.org/pdf/2304.10149).

+ Evaluating ChatGPT as a Recommender System: A Rigorous Approach, arxiv 2023, [[paper]](https://arxiv.org/pdf/2309.03613).

+ Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences, RecSys 2023 Short Paper, [[paper]](https://arxiv.org/pdf/2307.14225).

+ Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation, RecSys 2023 Short Paper, [[paper]](https://arxiv.org/pdf/2305.07609), [[code]](https://github.com/jizhi-zhang/FaiRLLM).

+ Uncovering ChatGPT's Capabilities in Recommender Systems, RecSys 2023 LBR, [[paper]](https://arxiv.org/pdf/2305.02182), [[code]](https://github.com/rainym00d/LLM4RS).

  



## Universal Representation Learning

**Github Repository: "Universal_user_representations for recommendation" [[link]](https://github.com/fajieyuan/universal_user_representation)**.

+ Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation, SIGIR 2020, [[paper]](https://arxiv.org/pdf/2001.04253), [[code]](https://github.com/fajieyuan/SIGIR2020_peterrec)

+ One Person, One Model, One World: Learning Continual User Representation without Forgetting, SIGIR 2021, [[paper]](https://arxiv.org/pdf/2009.13724.pdf), [[code]](https://github.com/fajieyuan/SIGIR2021_Conure) 

+ ID-Agnostic User Behavior Pre-training for Sequential Recommendation, CCIR 2022, [[paper]](https://arxiv.org/pdf/2206.02323).

+ Towards Universal Sequence Representation Learning for Recommender Systems, KDD 2022, [[paper]](https://arxiv.org/pdf/2206.05941), [[code]](https://github.com/RUCAIBox/UniSRec).

+ TransRec: learning transferable recommendation from mixture-of-modality feedback, arxiv 2022, [[paper]](https://arxiv.org/pdf/2206.06190).

+ Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders, WWW 2023, [[paper]](https://arxiv.org/pdf/2210.12316), [[code]](https://github.com/RUCAIBox/VQ-Rec).

+ One4all User Representation for Recommender Systems in E-commerce, arvix 2021, [[paper]](https://arxiv.org/pdf/2106.00573).

+ Text Is All You Need: Learning Language Representations for Sequential Recommendation, KDD 2023, [[paper]](https://arxiv.org/pdf/2305.13731).

+ Collaborative Large Language Model for Recommender Systems, arvix 2023, [[paper]](https://arxiv.org/pdf/2311.01343), [[code]](https://github.com/yaochenzhu/llm4rec).

  

## Generative Retrieval

+ A Simple Convolutional Generative Network for Next Item Recommendation, WSDM 2018/08, [[paper]](https://arxiv.org/pdf/1808.05163.pdf)  [[code]](https://github.com/fajieyuan/WSDM2019-nextitnet)

+ Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation, WWW 2020/04, [[paper]](https://arxiv.org/pdf/1906.04473.pdf)  [[code]](https://github.com/fajieyuan/WWW2020-grec)

+ Recommender Systems with Generative Retrieval, arvix 2023, [[paper]](https://arxiv.org/pdf/2305.05065).

+ Generative Sequential Recommendation with GPTRec, SIGIR 2023 workshop, [[paper]](https://arxiv.org/pdf/2306.11114).

+ Enhanced Generative Recommendation via Content and Collaboration Integration, arvix 2024, [[paper]](https://arxiv.org/pdf/2403.18480).



## Pretrain Language Model and Prompt Learning

**Survey paper: Pre-train, Prompt and Recommendation: A Comprehensive Survey of Language Modelling Paradigm Adaptations in Recommender Systems, arxiv 2023, [[paper]](https://arxiv.org/pdf/2302.03735).**

+ Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5), arvix 2022, [[paper]](https://arxiv.org/pdf/2203.13366),[[code]](https://github.com/jeykigung/P5).

+ Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective, SIGIR 2022, [[paper]](https://arxiv.org/pdf/2206.07353).

+ M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems, arvix 2022, [[paper]](https://arxiv.org/pdf/2205.08084).

+ Personalized Prompt for Sequential Recommendation, arvix 2022, [[paper]](https://arxiv.org/pdf/2205.09666).

+ Knowledge Prompt-tuning for Sequential Recommendation, ACM MM 2023, [[paper]](https://arxiv.org/pdf/2308.08459), [[code]](https://github.com/zhaijianyang/KP4SR).



## Dataset

+ Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation, arvix 2023, [[paper]](https://arxiv.org/pdf/2307.09688), [[KDD Cup 2023]](https://kddcup23.github.io/).

+ PixelRec: An Image Dataset for Benchmarking Recommender Systems with Raw Pixels, arvix 2023, [[paper]](https://arxiv.org/pdf/2309.06789), [[link]](https://github.com/westlake-repl/PixelRec).

+ NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation, arvix 2023, [[paper]](https://arxiv.org/pdf/2309.07705), [[link]](https://github.com/westlake-repl/NineRec).

+ A Content-Driven Micro-Video Recommendation Dataset at Scale, arvix 2023, [[paper]](https://arxiv.org/pdf/2309.15379), [[link]](https://github.com/westlake-repl/MicroLens).

+ EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation, arxiv, 2024[[paper]](https://arxiv.org/pdf/2404.01008)[[link]](https://anonymous.4open.science/r/Z-SV-CFB1)

+ MealRec : A Meal Recommendation Dataset with Meal-Course Affiliation for Personalization and Healthiness, arxiv 2024, [[paper]](http://arxiv.org/pdf/2404.05386).

+ MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation, SIGIR 2024, [[paper]](https://arxiv.org/pdf/2403.17876), [[link]](https://github.com/andreeaiana/xMIND).