Awesome-LLM-for-RecSys

Awesome-LLM-for-RecSys

Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.

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Awesome-LLM-for-RecSys Awesome

A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.

🎉 Our survey paper has been accepted by ACM Transactions on Information Systems (TOIS): How Can Recommender Systems Benefit from Large Language Models: A Survey

🔔 Since our survey paper is archived, we will update the latest research works at 1.7 Newest Research Work List.

😁 I am also wrting weekly paper notes about latest LLM-enhanced RS at WeChat. Welcome to follow by scanning the QR-Code.

🚀 2024.07.09 - Paper v6 released: Our archived camera-ready version for TOIS.

Survey Paper Update Logs

  • 2024.07.09 - Paper v6 released: Our camera-ready Version for TOIS, which will be archived.
  • 2024.02.05 - Paper v5 released: New release with 27-page main content & more thorough taxonomies.
  • 2023.06.29 - Paper v4 released: 7 papers have been newly added.
  • 2023.06.28 - Paper v3 released: Fix typos.
  • 2023.06.12 - Paper v2 released: Add summerization table in the appendix.
  • 2023.06.09 - Paper v1 released: Initial version.

1. Papers

We classify papers according to where LLM will be adapted in the pipeline of RS, which is summarized in the figure below.

1.1 LLM for Feature Engineering

1.1.1 User- and Item-level Feature Augmentation

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
LLM4KGC Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs PaLM (540B)/ ChatGPT Frozen Arxiv 2023 [Link]
TagGPT TagGPT: Large Language Models are Zero-shot Multimodal Taggers ChatGPT Frozen Arxiv 2023 [Link]
ICPC Large Language Models for User Interest Journeys LaMDA (137B) Full Finetuning/ Prompt Tuning Arxiv 2023 [Link]
KAR Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models ChatGPT Frozen Arxiv 2023 [Link]
PIE Product Information Extraction using ChatGPT ChatGPT Frozen Arxiv 2023 [Link]
LGIR Enhancing Job Recommendation through LLM-based Generative Adversarial Networks GhatGLM (6B) Frozen AAAI 2024 [Link]
GIRL Generative Job Recommendations with Large Language Model BELLE (7B) Full Finetuning Arxiv 2023 [Link]
LLM-Rec LLM-Rec: Personalized Recommendation via Prompting Large Language Models text-davinci-003 Frozen Arxiv 2023 [Link]
HKFR Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM ChatGPT Frozen RecSys 2023 [Link]
LLaMA-E LLaMA-E: Empowering E-commerce Authoring with Multi-Aspect Instruction Following LLaMA (30B) LoRA Arxiv 2023 [Link]
EcomGPT EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce BLOOMZ (7.1B) Full Finetuning Arxiv 2023 [Link]
TF-DCon Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation ChatGPT Frozen Arxiv 2023 [Link]
RLMRec Representation Learning with Large Language Models for Recommendation ChatGPT Frozen WWW 2024 [Link]
LLMRec LLMRec: Large Language Models with Graph Augmentation for Recommendation ChatGPT Frozen WSDM 2024 [Link]
LLMRG Enhancing Recommender Systems with Large Language Model Reasoning Graphs GPT4 Frozen Arxiv 2023 [Link]
CUP Recommendations by Concise User Profiles from Review Text ChatGPT Frozen Arxiv 2023 [Link]
SINGLE Modeling User Viewing Flow using Large Language Models for Article Recommendation ChatGPT Frozen Arxiv 2023 [Link]
SAGCN Understanding Before Recommendation: Semantic Aspect-Aware Review Exploitation via Large Language Models Vicuna (13B) Frozen Arxiv 2023 [Link]
UEM User Embedding Model for Personalized Language Prompting FLAN-T5-base (250M) Full Finetuning Arxiv 2024 [Link]
LLMHG LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation GPT4 Frozen Arxiv 2024 [Link]
Llama4Rec Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation LLaMA2 (7B) Full Finetuning Arxiv 2024 [Link]
LLM4Vis LLM4Vis: Explainable Visualization Recommendation using ChatGPT ChatGPT Frozen EMNLP 2023 [Link]
LoRec LoRec: Large Language Model for Robust Sequential Recommendation against Poisoning Attacks LLaMA2 Frozen SIGIR 2024 [Link]

1.1.2 Instance-level Sample Generation

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
GReaT Language Models are Realistic Tabular Data Generators GPT2-medium (355M) Full Finetuning ICLR 2023 [Link]
ONCE ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models ChatGPT Frozen WSDM 2024 [Link]
AnyPredict AnyPredict: Foundation Model for Tabular Prediction ChatGPT Frozen Arxiv 2023 [Link]
DPLLM Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models T5-XL (3B) Full Finetuning Arxiv 2023 [Link]
MINT Large Language Model Augmented Narrative Driven Recommendations text-davinci-003 Frozen RecSys 2023 [Link]
Agent4Rec On Generative Agents in Recommendation ChatGPT Frozen Arxiv 2023 [Link]
RecPrompt RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models GPT4 Frozen Arxiv 2023 [Link]
PO4ISR Large Language Models for Intent-Driven Session Recommendations ChatGPT Frozen Arxiv 2023 [Link]
BEQUE Large Language Model based Long-tail Query Rewriting in Taobao Search ChatGLM (6B) FFT Arxiv 2023 [Link]
Agent4Ranking Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLM ChatGPT Frozen Arxiv 2023 [Link]
PopNudge Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation ChatGPT Frozen Arxiv 2023 [Link]
1.2 LLM as Feature Encoder

1.2.1 Representation Enhancement

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
U-BERT U-BERT: Pre-training User Representations for Improved Recommendation BERT-base (110M) Full Finetuning AAAI 2021 [Link]
UNBERT UNBERT: User-News Matching BERT for News Recommendation BERT-base (110M) Full Finetuning IJCAI 2021 [Link]
PLM-NR Empowering News Recommendation with Pre-trained Language Models RoBERTa-base (125M) Full Finetuning SIGIR 2021 [Link]
Pyramid-ERNIE Pre-trained Language Model based Ranking in Baidu Search ERNIE (110M) Full Finetuning KDD 2021 [Link]
ERNIE-RS Pre-trained Language Model for Web-scale Retrieval in Baidu Search ERNIE (110M) Full Finetuning KDD 2021 [Link]
CTR-BERT CTR-BERT: Cost-effective knowledge distillation for billion-parameter teacher models Customized BERT (1.5B) Full Finetuning ENLSP 2021 [Link]
SuKD Learning Supplementary NLP Features for CTR Prediction in Sponsored Search RoBERTa-large (355M) Full Finetuning KDD 2022 [Link]
PREC Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation BERT-base (110M) Full Finetuning COLING 2022 [Link]
MM-Rec MM-Rec: Visiolinguistic Model Empowered Multimodal News Recommendation BERT-base (110M) Full Finetuning SIGIR 2022 [Link]
Tiny-NewsRec Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation UniLMv2-base (110M) Full Finetuning EMNLP 2022 [Link]
PLM4Tag PTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained Models CodeBERT (125M) Full Finetuning ICPC 2022 [Link]
TwHIN-BERT TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations BERT-base (110M) Full Finetuning Arxiv 2022 [Link]
LSH Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study BERT-base (110M) Full Finetuning Arxiv 2023 [Link]
LLM2BERT4Rec Leveraging Large Language Models for Sequential Recommendation text-embedding-ada-002 Frozen RecSys 2023 [Link]
LLM4ARec Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations GPT2 (110M) Prompt Tuning Arxiv 2023 [Link]
TIGER Recommender Systems with Generative Retrieval Sentence-T5-base (223M) Frozen NIPS 2023 [Link]
TBIN TBIN: Modeling Long Textual Behavior Data for CTR Prediction BERT-base (110M) Frozen DLP-RecSys 2023 [Link]
LKPNR LKPNR: LLM and KG for Personalized News Recommendation Framework LLaMA2 (7B) Frozen Arxiv 2023 [Link]
SSNA Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation DistilRoBERTa-base (83M) Layerwise Adapter Tuning Arxiv 2023 [Link]
CollabContext Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model Instructor-XL (1.5B) Frozen Arxiv 2023 [Link]
LMIndexer Language Models As Semantic Indexers T5-base (223M) Full Finetuning Arxiv 2023 [Link]
Stack A BERT based Ensemble Approach for Sentiment Classification of Customer Reviews and its Application to Nudge Marketing in e-Commerce BERT-base (110M) Frozen Arxiv 2023 [Link]
N/A Utilizing Language Models for Tour Itinerary Recommendation BERT-base (110M) Full Finetuning PMAI@IJCAI 2023 [Link]
UEM User Embedding Model for Personalized Language Prompting Sentence-T5-base (223M) Frozen Arxiv 2024 [Link]
Social-LLM Social-LLM: Modeling User Behavior at Scale using Language Models and Social Network Data SBERT-MPNet-base (110M) Frozen Arxiv 2024 [Link]
LLMRS LLMRS: Unlocking Potentials of LLM-Based Recommender Systems for Software Purchase MPNet (110M) Frozen Arxiv 2024 [Link]
KERL Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems BERT-mini Frozen TNNLS [Link]
N/A Empowering Few-Shot Recommender Systems with Large Language Models -- Enhanced Representations ChatGPT Frozen IEEE Access [Link]
N/A Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations Unknown Frozen Arxiv 2023 [Link]

1.2.2 Unified Cross-domain Recommendation

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
ZESRec Zero-Shot Recommender Systems BERT-base (110M) Frozen Arxiv 2021 [Link]
UniSRec Towards Universal Sequence Representation Learning for Recommender Systems BERT-base (110M) Frozen KDD 2022 [Link]
TransRec TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback BERT-base (110M) Full Finetuning Arxiv 2022 [Link]
VQ-Rec Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders BERT-base (110M) Frozen WWW 2023 [Link]
IDRec vs MoRec Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited BERT-base (110M) Full Finetuning SIGIR 2023 [Link]
TransRec Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights RoBERTa-base (125M) Layerwise Adapter Tuning Arxiv 2023 [Link]
TCF Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights OPT-175B (175B) Frozen/ Full Finetuning Arxiv 2023 [Link]
S&R Foundation An Unified Search and Recommendation Foundation Model for Cold-Start Scenario ChatGLM (6B) Frozen CIKM 2023 [Link]
MISSRec MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation CLIP-B/32 (400M) Full Finetuning MM 2023 [Link]
UFIN UFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate Prediction FLAN-T5-base (250M) Frozen Arxiv 2023 [Link]
PMMRec Multi-Modality is All You Need for Transferable Recommender Systems RoBERTa-large (355M) Top-2-layer Finetuning ICDE 2024 [Link]
Uni-CTR A Unified Framework for Multi-Domain CTR Prediction via Large Language Models Sheared-LLaMA (1.3B) LoRA Arxiv 2023 [Link]
PCDR Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation BERT-base (110M) Frozen WWW 2024 [Link]
1.3 LLM as Scoring/Ranking Function

1.3.1 Item Scoring Task

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
LMRecSys Language Models as Recommender Systems: Evaluations and Limitations GPT2-XL (1.5B) Full Finetuning ICBINB 2021 [Link]
PTab PTab: Using the Pre-trained Language Model for Modeling Tabular Data BERT-base (110M) Full Finetuning Arxiv 2022 [Link]
UniTRec UniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based Recommendation BART (406M) Full Finetuning ACL 2023 [Link]
Prompt4NR Prompt Learning for News Recommendation BERT-base (110M) Full Finetuning SIGIR 2023 [Link]
RecFormer Text Is All You Need: Learning Language Representations for Sequential Recommendation LongFormer (149M) Full Finetuning KDD 2023 [Link]
TabLLM TabLLM: Few-shot Classification of Tabular Data with Large Language Models T0 (11B) Few-shot Parameter-effiecnt Finetuning AISTATS 2023 [Link]
Zero-shot GPT Zero-Shot Recommendation as Language Modeling GPT2-medium (355M) Frozen Arxiv 2023 [Link]
FLAN-T5 Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction FLAN-5-XXL (11B) Full Finetuning Arxiv 2023 [Link]
BookGPT BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model ChatGPT Frozen Arxiv 2023 [Link]
TALLRec TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation LLaMA (7B) LoRA RecSys 2023 [Link]
PBNR PBNR: Prompt-based News Recommender System T5-small (60M) Full Finetuning Arxiv 2023 [Link]
CR-SoRec CR-SoRec: BERT driven Consistency Regularization for Social Recommendation BERT-base (110M) Full Finetuning RecSys 2023 [Link]
PromptRec Towards Personalized Cold-Start Recommendation with Prompts LLaMA (7B) Frozen Arxiv 2023 [Link]
GLRec Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations BELLE-LLaMA (7B) LoRA Arxiv 2023 [Link]
BERT4CTR BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction RoBERTa-large (355M) Full Finetuning KDD 2023 [Link]
ReLLa ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation Vicuna (13B) LoRA WWW 2024 [Link]
TASTE Text Matching Improves Sequential Recommendation by Reducing Popularity Biases T5-base (223M) Full Finetuning CIKM 2023 [Link]
N/A Unveiling Challenging Cases in Text-based Recommender Systems BERT-base (110M) Full Finetuning RecSys Workshop 2023 [Link]
ClickPrompt ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction RoBERTa-large (355M) Full Finetuning WWW 2024 [Link]
SetwiseRank A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models FLAN-T5-XXL (11B) Frozen Arxiv 2023 [Link]
UPSR Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language T5-base (223M) Full Finetuning Arxiv 2023 [Link]
LLM-Rec One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems OPT (6.7B) LoRA Arxiv 2023 [Link]
LLMRanker Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels FLAN PaLM2 S Frozen Arxiv 2023 [Link]
CoLLM CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation Vicuna (7B) LoRA Arxiv 2023 [Link]
FLIP FLIP: Towards Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction RoBERTa-large (355M) Full Finetuning Arxiv 2023 [Link]
BTRec BTRec: BERT-Based Trajectory Recommendation for Personalized Tours BERT-base (110M) Full Finetuning Arxiv 2023 [Link]
CLLM4Rec Collaborative Large Language Model for Recommender Systems GPT2 (110M) Full Finetuning Arxiv 2023 [Link]
CUP Recommendations by Concise User Profiles from Review Text BERT-base (110M) Last-layer Finetuning Arxiv 2023 [Link]
N/A Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers FLAN-T5-XL (3B) Full Finetuning Arxiv 2023 [Link]
CoWPiRec Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation BERT-base (110M) Full Finetuning ICDM 2023 [Link]
RecExplainer RecExplainer: Aligning Large Language Models for Recommendation Model Interpretability Vicuna-v1.3 (7B) LoRA Arxiv 2023 [Link]
E4SRec E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation LLaMA2 (13B) LoRA Arxiv 2023 [Link]
CER The Problem of Coherence in Natural Language Explanations of Recommendations GPT2 (110M) Full Finetuning ECAI 2023 [Link]
LSAT Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems LLaMA (7B) LoRA Arxiv 2023 [Link]
Llama4Rec Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation LLaMA2 (7B) Full Finetuning Arxiv 2024 [Link]

1.3.2 Item Generation Task

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
GPT4Rec GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation GPT2 (110M) Full Finetuning Arxiv 2023 [Link]
VIP5 VIP5: Towards Multimodal Foundation Models for Recommendation T5-base (223M) Layerwise Adater Tuning EMNLP 2023 [Link]
P5-ID How to Index Item IDs for Recommendation Foundation Models T5-small (60M) Full Finetuning Arxiv 2023 [Link]
FaiRLLM Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation ChatGPT Frozen RecSys 2023 [Link]
PALR PALR: Personalization Aware LLMs for Recommendation LLaMA (7B) Full Finetuning Arxiv 2023 [Link]
ChatGPT Large Language Models are Zero-Shot Rankers for Recommender Systems ChatGPT Frozen ECIR 2024 [Link]
AGR Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT ChatGPT Frozen Arxiv 2023 [Link]
NIR Zero-Shot Next-Item Recommendation using Large Pretrained Language Models GPT3 (175B) Frozen Arxiv 2023 [Link]
GPTRec Generative Sequential Recommendation with GPTRec GPT2-medium (355M) Full Finetuning Gen-IR@SIGIR 2023 [Link]
ChatNews A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News ChatGPT Frozen Arxiv 2023 [Link]
N/A Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences PaLM (62B) Frozen RecSys 2023 [Link]
LLMSeqPrompt Leveraging Large Language Models for Sequential Recommendation OpenAI ada model Finetune RecSys 2023 [Link]
GenRec GenRec: Large Language Model for Generative Recommendation LLaMA (7B) LoRA Arxiv 2023 [Link]
UP5 UP5: Unbiased Foundation Model for Fairness-aware Recommendation T5-base (223M) Prefix Tuning Arxiv 2023 [Link]
HKFR Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM ChatGLM (6B) LoRA RecSys 2023 [Link]
N/A The Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations ChatGPT Frozen EAAMO 2023 [Link]
BIGRec A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems LLaMA (7B) LoRA Arxiv 2023 [Link]
KP4SR Knowledge Prompt-tuning for Sequential Recommendation T5-small (60M) Full Finetuning Arxiv 2023 [Link]
RecSysLLM Leveraging Large Language Models for Pre-trained Recommender Systems GLM (10B) LoRA Arxiv 2023 [Link]
POD Prompt Distillation for Efficient LLM-based Recommendation T5-small (60M) Full Finetuning CIKM 2023 [Link]
N/A Evaluating ChatGPT as a Recommender System: A Rigorous Approach ChatGPT Frozen Arxiv 2023 [Link]
RaRS Retrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language Models ChatGPT Frozen RecSys Doctoral Symposium 2023 [Link]
JobRecoGPT JobRecoGPT -- Explainable job recommendations using LLMs GPT4 Frozen Arxiv 2023 [Link]
LANCER Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling GPT2 (110M) Prefix Tuning Arxiv 2023 [Link]
TransRec A Multi-facet Paradigm to Bridge Large Language Model and Recommendation LLaMA (7B) LoRA Arxiv 2023 [Link]
AgentCF AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems text-davinci-003 & gpt-3.5-turbo Frozen WWW 2024 [Link]
P4LM Factual and Personalized Recommendations using Language Models and Reinforcement Learning PaLM2-XS Full Finetuning Arxiv 2023 [Link]
InstructMK Multiple Key-value Strategy in Recommendation Systems Incorporating Large Language Model LLaMA (7B) Full Finetuning CIKM GenRec 2023 [Link]
LightLM LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation T5-small (60M) Full Finetuning Arxiv 2023 [Link]
LlamaRec LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking LLaMA2 (7B) QLoRA PGAI@CIKM 2023 [Link]
N/A Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study GPT-4V Frozen Arxiv 2023 [Link]
N/A Exploring Fine-tuning ChatGPT for News Recommendation ChatGPT gpt-3.5-turbo finetuning API Arxiv 2023 [Link]
N/A Do LLMs Implicitly Exhibit User Discrimination in Recommendation? An Empirical Study ChatGPT Frozen Arxiv 2023 [Link]
LC-Rec Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation LLaMA (7B) LoRA Arxiv 2023 [Link]
DOKE Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations ChatGPT Frozen Arxiv 2023 [Link]
ControlRec ControlRec: Bridging the Semantic Gap between Language Model and Personalized Recommendation T5-base (223M) Full Finetuning Arxiv 2023 [Link]
LLaRA LLaRA: Large Language-Recommendation Assistant LLaMA2 (7B) LoRA SIGIR 2024 [Link]
PO4ISR Large Language Models for Intent-Driven Session Recommendations ChatGPT Frozen Arxiv 2023 [Link]
DRDT DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation ChatGPT Frozen Arxiv 2023 [Link]
RecPrompt RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models GPT4 Frozen Arxiv 2023 [Link]
LiT5 Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models T5-XL (3B) Full Finetuning Arxiv 2023 [Link]
STELLA Large Language Models are Not Stable Recommender Systems ChatGPT Frozen Arxiv 2023 [Link]
Llama4Rec Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation LLaMA2 (7B) Full Finetuning Arxiv 2024 [Link]
RECLLM Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recency ChatGPT Frozen Arxiv 2024 [Link]
DEALRec Data-efficient Fine-tuning for LLM-based Recommendation LLaMA (7B) LoRA Arxiv 2024 [Link]

1.3.3 Hybrid Task

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
P5 Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) T5-base (223M) Full Finetuning RecSys 2022 [Link]
M6-Rec M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems M6-base (300M) Option Tuning Arxiv 2022 [Link]
InstructRec Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach FLAN-T5-XL (3B) Full Finetuning Arxiv 2023 [Link]
ChatGPT Is ChatGPT a Good Recommender? A Preliminary Study ChatGPT Frozen Arxiv 2023 [Link]
ChatGPT Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent ChatGPT Frozen Arxiv 2023 [Link]
ChatGPT Uncovering ChatGPT's Capabilities in Recommender Systems ChatGPT Frozen RecSys 2023 [Link]
BDLM Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation Vicuna (7B) Full Finetuning Arxiv 2023 [Link]
RecRanker RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation LLaMA2 (13B) Full Finetuning Arxiv 2023 [Link]
1.4 LLM for User Interaction

1.4.1 Task-oriented User Interaction

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
TG-ReDial Towards Topic-Guided Conversational Recommender System BERT-base (110M) & GPT2 (110M) Unknown COLING 2020 [Link]
TCP Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems BERT-base (110M) Full Finetuning Arxiv 2022 [Link]
MESE Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta-Information DistilBERT (67M) & GPT2 (110M) Full Finetuning ACL 2022 [Link]
UniMIND A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems BART-base (139M) Full Finetuning ACM TOIS 2023 [Link]
VRICR Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation BERT-base (110M) Full Finetuning WSDM 2023 [Link]
KECR Explicit Knowledge Graph Reasoning for Conversational Recommendation BERT-base (110M) & GPT2 (110M) Frozen ACM TIST 2023 [Link]
N/A Large Language Models as Zero-Shot Conversational Recommenders GPT4 Frozen CIKM 2023 [Link]
MuseChat MuseChat: A Conversational Music Recommendation System for Videos Vicuna (7B) LoRA Arxiv 2023 [Link]
N/A Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue Chinese-Alpaca (7B) LoRA EMNLP 2023 Findings [Link]
N/A ChatGPT for Conversational Recommendation: Refining Recommendations by Reprompting with Feedback ChatGPT Frozen Arxiv 2024 [Link]

1.4.2 Open-ended User Interaction

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
BARCOR BARCOR: Towards A Unified Framework for Conversational Recommendation Systems BART-base (139M) Selective-layer Finetuning Arxiv 2022 [Link]
RecInDial RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models DialoGPT (110M) Full Finetuning AACL 2022 [Link]
UniCRS Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning DialoGPT-small (176M) Frozen KDD 2022 [Link]
T5-CR Multi-Task End-to-End Training Improves Conversational Recommendation T5-base (223M) Full Finetuning Arxiv 2023 [Link]
TtW Talk the Walk: Synthetic Data Generation for Conversational Music Recommendation T5-base (223M) & T5-XXL (11B) Full Finetuning & Frozen Arxiv 2023 [Link]
N/A Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models ChatGPT Frozen EMNLP 2023 [Link]
PECRS Parameter-Efficient Conversational Recommender System as a Language Processing Task GPT2-medium (355M) LoRA EACL 2024 [Link]
1.5 LLM for RS Pipeline Controller

Name Paper LLM Backbone (Largest) LLM Tuning Strategy Publication Link
Chat-REC Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System ChatGPT Frozen Arxiv 2023 [Link]
RecLLM Leveraging Large Language Models in Conversational Recommender Systems LLaMA (7B) Full Finetuning Arxiv 2023 [Link]
RAH RAH! RecSys-Assistant-Human: A Human-Central Recommendation Framework with Large Language Models GPT4 Frozen Arxiv 2023 [Link]
RecMind RecMind: Large Language Model Powered Agent For Recommendation ChatGPT Frozen NAACL 2024 [Link]
InteRecAgent Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations GPT4 Frozen Arxiv 2023 [Link]
CORE Lending Interaction Wings to Recommender Systems with Conversational Agents N/A N/A NIPS 2023 [Link]
LLMCRS A Large Language Model Enhanced Conversational Recommender System LLaMA (7B) Full Finetuning Arxiv 2023 [Link]
1.6 Related Survey Papers

Paper Publication Link
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era KDD 2024 [Link]
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era Arxiv 2024 [Link]
Survey for Landing Generative AI in Social and E-commerce Recsys - the Industry Perspectives Arxiv 2024 [Link]
A Survey of Generative Search and Recommendation in the Era of Large Language Models Arxiv 2024 [Link]
When Search Engine Services meet Large Language Models: Visions and Challenges Arxiv 2024 [Link]
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys) Arxiv 2024 [Link]
Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review Arxiv 2024 [Link]
Foundation Models for Recommender Systems: A Survey and New Perspectives Arxiv 2024 [Link]
Prompting Large Language Models for Recommender Systems: A Comprehensive Framework and Empirical Analysis Arixv 2024 [Link]
User Modeling in the Era of Large Language Models: Current Research and Future Directions IEEE Data Engineering Bulletin 2023 [Link]
A Survey on Large Language Models for Personalized and Explainable Recommendations Arxiv 2023 [Link]
Large Language Models for Generative Recommendation: A Survey and Visionary Discussions Arxiv 2023 [Link]
Large Language Models for Information Retrieval: A Survey Arxiv 2023 [Link]
When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities Arxiv 2023 [Link]
Recommender Systems in the Era of Large Language Models (LLMs) Arxiv 2023 [Link]
A Survey on Large Language Models for Recommendation Arxiv 2023 [Link]
Pre-train, Prompt and Recommendation: A Comprehensive Survey of Language Modelling Paradigm Adaptations in Recommender Systems TACL 2023 [Link]
Self-Supervised Learning for Recommender Systems: A Survey TKDE 2022 [Link]
1.7 Newest Research Work List

Paper Publication Link
Large Language Model Can Interpret Latent Space of Sequential Recommender Arxiv 2023 [Link]
Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging Arxiv 2023 [Link]
INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning Arxiv 2024 [Link]
Evaluation of Synthetic Datasets for Conversational Recommender Systems Arxiv 2023 [Link]
Generative Recommendation: Towards Next-generation Recommender Paradigm Arxiv 2023 [Link]
Towards Personalized Prompt-Model Retrieval for Generative Recommendation Arxiv 2023 [Link]
Generative Next-Basket Recommendation RecSys 2023 [Link]
Unlocking the Potential of Large Language Models for Explainable Recommendations Arxiv 2023 [Link]
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs Falcon (40B) Frozen
Improving Sequential Recommendations with LLMs Arxiv 2024 [Link]
A Multi-Agent Conversational Recommender System Arxiv 2024 [Link]
TransFR: Transferable Federated Recommendation with Pre-trained Language Models Arxiv 2024 [Link]
Large Language Model Distilling Medication Recommendation Model Arxiv 2024 [Link]
Uncertainty-Aware Explainable Recommendation with Large Language Models Arxiv 2024 [Link]
Natural Language User Profiles for Transparent and Scrutable Recommendations Arxiv 2024 [Link]
Leveraging LLMs for Unsupervised Dense Retriever Ranking Arxiv 2024 [Link]
RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation Arxiv 2024 [Link]
A Multi-Agent Conversational Recommender System Arxiv 2024 [Link]
Fairly Evaluating Large Language Model-based Recommendation Needs Revisit the Cross-Entropy Loss Arxiv 2024 [Link]
SearchAgent: A Lightweight Collaborative Search Agent with Large Language Models Arxiv 2024 [Link]
Large Language Model Interaction Simulator for Cold-Start Item Recommendation Arxiv 2024 [Link]
Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation Arxiv 2024 [Link]
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data Arxiv 2024 [Link]
LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations Arxiv 2024 [Link]
LLM-based Federated Recommendation Arxiv 2024 [Link]
Rethinking Large Language Model Architectures for Sequential Recommendations Arxiv 2024 [Link]
Large Language Model with Graph Convolution for Recommendation Arxiv 2024 [Link]
Rec-GPT4V: Multimodal Recommendation with Large Vision-Language Models Arxiv 2024 [Link]
Enhancing Recommendation Diversity by Re-ranking with Large Language Models Arxiv 2024 [Link]
Are ID Embeddings Necessary? Whitening Pre-trained Text Embeddings for Effective Sequential Recommendation Arxiv 2024 [Link]
SPAR: Personalized Content-Based Recommendation via Long Engagement Attention Arxiv 2024 [Link]
Cognitive Personalized Search Integrating Large Language Models with an Efficient Memory Mechanism WWW 2024 [Link]
Large Language Models as Data Augmenters for Cold-Start Item Recommendation Arxiv 2024 [Link]
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from Large Language Models Arxiv 2024 [Link]
LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based Recommendation Arxiv 2024 [Link]
Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph Arxiv 2024 [Link]
User-LLM: Efficient LLM Contextualization with User Embeddings Arxiv 2024 [Link]
Stealthy Attack on Large Language Model based Recommendation Arxiv 2024 [Link]
Multi-Agent Collaboration Framework for Recommender Systems Arxiv 2024 [Link]
Item-side Fairness of Large Language Model-based Recommendation System WWW 2024 [Link]
Integrating Large Language Models with Graphical Session-Based Recommendation Arxiv 2024 [Link]
Language-Based User Profiles for Recommendation LLM-IGS@WSDM2024 [Link]
BASES: Large-scale Web Search User Simulation with Large Language Model based Agents Arxiv 2024 [Link]
Prospect Personalized Recommendation on Large Language Model-based Agent Platform Arxiv 2024 [Link]
Sequence-level Semantic Representation Fusion for Recommender Systems Arxiv 2024 [Link]
Corpus-Steered Query Expansion with Large Language Models ECAL 2024 [Link]
NoteLLM: A Retrievable Large Language Model for Note Recommendation WWW 2024 [Link]
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce WWW 2024 [Link]
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction Arxiv 2024 [Link]
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning Arxiv 2024 [Link]
InteraRec: Interactive Recommendations Using Multimodal Large Language Models Arxiv 2024 [Link]
ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework CHASE 2024 [Link]
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation Arxiv 2024 [Link]
Generative News Recommendation WWW 2024 [Link]
Bridging Language and Items for Retrieval and Recommendation Arxiv 2024 [Link]
Can Small Language Models be Good Reasoners for Sequential Recommendation? WWW 2024 [Link]
Aligning Large Language Models for Controllable Recommendations Arxiv 2024 [Link]
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks WWW 2024 [Link]
Towards Graph Foundation Models for Personalization Arxiv 2024 [Link]
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System Arxiv 2024 [Link]
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation Arxiv 2024 [Link]
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems WWW 2024 Demo [Link]
KELLMRec: Knowledge-Enhanced Large Language Models for Recommendation Arxiv 2024 [Link]
USimAgent: Large Language Models for Simulating Search Users Arxiv 2024 [Link]
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation Arxiv 2024 [Link]
Integrating Large Language Models with Graphical Session-Based Recommendation Arxiv 2024 [Link]
Language-Based User Profiles for Recommendation LLM-IGS@WSDM2024 [Link]
BASES: Large-scale Web Search User Simulation with Large Language Model based Agents Arxiv 2024 [Link]
Prospect Personalized Recommendation on Large Language Model-based Agent Platform Arxiv 2024 [Link]
Sequence-level Semantic Representation Fusion for Recommender Systems Arxiv 2024 [Link]
Corpus-Steered Query Expansion with Large Language Models EACL 2024 [Link]
NoteLLM: A Retrievable Large Language Model for Note Recommendation WWW 2024 [Link]
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce WWW 2024 [Link]
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction SIGIR 2024 [Link]
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning SIGIR 2024 [Link]
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation FCS [Link]
Generative News Recommendation WWW 2024 [Link]
Bridging Language and Items for Retrieval and Recommendation Arxiv 2024 [Link]
Can Small Language Models be Good Reasoners for Sequential Recommendation? WWW 2024 [Link]
Aligning Large Language Models for Controllable Recommendations Arxiv 2024 [Link]
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks WWW 2024 [Link]
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System Arxiv 2024 [Link]
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation Arxiv 2024 [Link]
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems WWW 2024 [Link]
KELLMRec: Knowledge-Enhanced Large Language Models for Recommendation Arxiv 2024 [Link]
Towards Graph Foundation Models for Personalization Arxiv 2024 [Link]
USimAgent: Large Language Models for Simulating Search Users Arxiv 2024 [Link]
The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendation NAACL 2024 [Link]
PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction WWW 2024 [Link]
Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation Arxiv 2024 [Link]
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond ICLR 2024 [Link]
Harnessing Large Language Models for Text-Rich Sequential Recommendation Arxiv 2024 [Link]
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment Recommendation Arxiv 2024 [Link]
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendations Arxiv 2024 [Link]
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models Arxiv 2024 [Link]
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling Arxiv 2024 [Link]
Large Language Models Enhanced Collaborative Filtering Arxiv 2024 [Link]
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users LREC-COLING 2024 [Link]
Sequential Recommendation with Latent Relations based on Large Language Model Arxiv 2024 [Link]
Enhanced Generative Recommendation via Content and Collaboration Integration Arxiv 2024 [Link]
To Recommend or Not: Recommendability Identification in Conversations with Pre-trained Language Models Arxiv 2024 [Link]
IDGenRec: LLM-RecSys Alignment with Textual ID Learning SIGIR 2024 [Link]
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors SIGIR 2024 [Link]
Make Large Language Model a Better Ranker Arxiv 2024 [Link]
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers NAACL 2024 [Link]
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT SIGIR 2024 [Link]
Where to Move Next: Zero-shot Generalization of LLMs for Next POI Recommendation Arxiv 2024 [Link]
Tired of Plugins? Large Language Models Can Be End-To-End Recommender Arxiv 2024 [Link]
Aligning Large Language Models with Recommendation Knowledge NAACL 2024 [Link]
Enhancing Content-based Recommendation via Large Language Model Arxiv 2024 [Link]
DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level Arxiv 2024 [Link]
Optimization Methods for Personalizing Large Language Models through Retrieval Augmentation Arxiv 2024 [Link]
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models Arxiv 2024 [Link]
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer Arxiv 2024 [Link]
PMG : Personalized Multimodal Generation with Large Language Models Arxiv 2024 [Link]
The Elephant in the Room: Rethinking the Usage of Pre-trained Language Model in Sequential Recommendation Arxiv 2024 [Link]
Exact and Efficient Unlearning for Large Language Model-based Recommendation Arxiv 2024 [Link]
Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System Arxiv 2024 [Link]
Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommendation Systems SIGIR 2024 [Link]
Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers Arxiv 2024 [Link]
RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm Arxiv 2024 [Link]
MMGRec: Multimodal Generative Recommendation with Transformer Model Arxiv 2024 [Link]
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search Arxiv 2024 [Link]
Contrastive Quantization based Semantic Code for Generative Recommendation Arxiv 2024 [Link]
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction Arxiv 2024 [Link]
Large Language Models for Next Point-of-Interest Recommendation SIGIR 2024 [Link]
Ranked List Truncation for Large Language Model-based Re-Ranking SIGIR 2024 [Link]
Large Language Models as Conversational Movie Recommenders: A User Study Arxiv 2024 [Link]
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model Arxiv 2024 [Link]
Efficient and Responsible Adaptation of Large Language Models for Robust Top-k Recommendations Arxiv 2024 [Link]
FairEvalLLM. A Comprehensive Framework for Benchmarking Fairness in Large Language Model Recommender Systems Arxiv 2024 [Link]
Improve Temporal Awareness of LLMs for Sequential Recommendation Arxiv 2024 [Link]
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation Arxiv 2024 [Link]
Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application Arxiv 2024 [Link]
DynLLM: When Large Language Models Meet Dynamic Graph Recommendation Arxiv 2024 [Link]
Learnable Tokenizer for LLM-based Generative Recommendation Arxiv 2024 [Link]
CELA: Cost-Efficient Language Model Alignment for CTR Prediction Arxiv 2024 [Link]
RDRec: Rationale Distillation for LLM-based Recommendation ACL 2024 [Link]
EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations Arxiv 2024 [Link]
Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation Arxiv 2024 [Link]
RecGPT: Generative Pre-training for Text-based Recommendation ACL 2024 [Link]
Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning SIGIR 2024 [Link]
Finetuning Large Language Model for Personalized Ranking Arxiv 2024 [Link]
LLMs for User Interest Exploration: A Hybrid Approach Arxiv 2024 [Link]
NoteLLM-2: Multimodal Large Representation Models for Recommendation Arxiv 2024 [Link]
Multimodality Invariant Learning for Multimedia-Based New Item Recommendation Arxiv 2024 [Link]
SLMRec: Empowering Small Language Models for Sequential Recommendation Arxiv 2024 [Link]
Keyword-driven Retrieval-Augmented Large Language Models for Cold-start User Recommendations Arxiv 2024 [Link]
Generating Query Recommendations via LLMs Arxiv 2024 [Link]
Large Language Models Enhanced Sequential Recommendation for Long-tail User and Item Arxiv 2024 [Link]
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation KDD 2024 [Link]
LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based Ranking Arxiv 2024 [Link]
A Practice-Friendly Two-Stage LLM-Enhanced Paradigm in Sequential Recommendation Arxiv 2024 [Link]
Large Language Models as Recommender Systems: A Study of Popularity Bias Gen-IR@SIGIR24 [Link]
Privacy in LLM-based Recommendation: Recent Advances and Future Directions Arxiv 2024 [Link]
An LLM-based Recommender System Environment Arxiv 2024 [Link]
Robust Interaction-based Relevance Modeling for Online E-Commerce and LLM-based Retrieval ECML-PKDD 2024 [Link]
Large Language Models Make Sample-Efficient Recommender Systems FCS [Link]
XRec: Large Language Models for Explainable Recommendation Arxiv 2024 [Link]
Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation Arxiv 2024 [Link]
Large Language Models as Evaluators for Recommendation Explanations Arxiv 2024 [Link]
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation ACL 2024 [Link]
Item-Language Model for Conversational Recommendation Arxiv 2024 [Link]
Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens Arxiv 2024 [Link]
On Softmax Direct Preference Optimization for Recommendation Arxiv 2024 [Link]
TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation Arxiv 2024 [Link]
DELRec: Distilling Sequential Pattern to Enhance LLM-based Recommendation Arxiv 2024 [Link]
TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy Arxiv 2024 [Link]
Multi-Layer Ranking with Large Language Models for News Source Recommendation SIGIR 2024 [Link]
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval Arxiv 2024 [Link]
LLM-enhanced Reranking in Recommender Systems Arxiv 2024 [Link]
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation Arxiv 2024 [Link]
Taxonomy-Guided Zero-Shot Recommendations with LLMs Arxiv 2024 [Link]
EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration KDD 2024 [Link]
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers Arxiv 2024 [Link]
Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning KDD 2024 [Link]
Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learning Arxiv 2024 [Link]
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation Arxiv 2024 [Link]
FIRST: Faster Improved Listwise Reranking with Single Token Decoding Arxiv 2024 [Link]
LLM-Powered Explanations: Unraveling Recommendations Through Subgraph Reasoning Arxiv 2024 [Link]
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task Arxiv 2024 [Link]
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation Arxiv 2024 [Link]
Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM Optimizers ACL 2024 [Link]
ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification Questions Arxiv 2024 [Link]
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models Arxiv 2024 [Link]
Preference Distillation for Personalized Generative Recommendation Arxiv 2024 [Link]
Towards Bridging the Cross-modal Semantic Gap for Multi-modal Recommendation Arxiv 2024 [Link]
Language Models Encode Collaborative Signals in Recommendation Arxiv 2024 [Link]
A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Model Arxiv 2024 [Link]
LLMGR: Large Language Model-based Generative Retrieval in Alipay Search SIGIR 2024 [Link]
Enhancing Sequential Recommenders with Augmented Knowledge from Aligned Large Language Models SIGIR 2024 [Link]
Reinforced Prompt Personalization for Recommendation with Large Language Models Arxiv 2024 [Link]
Improving Retrieval in Sponsored Search by Leveraging Query Context Signals Arxiv 2024 [Link]
Generative Retrieval with Preference Optimization for E-commerce Search Arxiv 2024 [Link]
GenRec: Generative Personalized Sequential Recommendation Arxiv 2024 [Link]
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval Arxiv 2024 [Link]
Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insights CIKM 2024 [Link]
Leveraging LLM Reasoning Enhances Personalized Recommender Systems ACL 2024 [Link]
Multi-Aspect Reviewed-Item Retrieval via LLM Query Decomposition and Aspect Fusion Arxiv 2024 [Link]
Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation Arxiv 2024 [Link]
Exploring Query Understanding for Amazon Product Search Arxiv 2024 [Link]
A Decoding Acceleration Framework for Industrial Deployable LLM-based Recommender Systems Arxiv 2024 [Link]
Prompt Tuning as User Inherent Profile Inference Machine Arxiv 2024 [Link]
Beyond Inter-Item Relations: Dynamic Adaptive Mixture-of-Experts for LLM-Based Sequential Recommendation Arxiv 2024 [Link]
Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation Arxiv 2024 [Link]
DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System Arxiv 2024 [Link]
LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation Arxiv 2024 [Link]
EasyRec: Simple yet Effective Language Models for Recommendation Arxiv 2024 [Link]
Collaborative Cross-modal Fusion with Large Language Model for Recommendation CIKM 2024 [Link]
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation Arxiv 2024 [Link]
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models Arxiv 2024 [Link]
CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation Arxiv 2024 [Link]
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts Arxiv 2024 [Link]
Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation Arxiv 2024 [Link]
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems Arxiv [Link]
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding RecSys 2024 [Link]
SC-Rec: Enhancing Generative Retrieval with Self-Consistent Reranking for Sequential Recommendation Arxiv 2024 [Link]
Are LLM-based Recommenders Already the Best? Simple Scaled Cross-entropy Unleashes the Potential of Traditional Sequential Recommenders Arxiv 2024 [Link]
HRGraph: Leveraging LLMs for HR Data Knowledge Graphs with Information Propagation-based Job Recommendation KaLLM 2024 [Link]
An Extremely Data-efficient and Generative LLM-based Reinforcement Learning Agent for Recommenders Arxiv 2024 [Link]
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent KDD 2024 [Link]
Laser: Parameter-Efficient LLM Bi-Tuning for Sequential Recommendation with Collaborative Information Arxiv 2024 [Link]
MARS: Matching Attribute-aware Representations for Text-based Sequential Recommendation CIKM 2024 [Link]
End-to-End Learnable Item Tokenization for Generative Recommendation Arxiv 2024 [Link]
Incorporate LLMs with Influential Recommender System Arxiv 2024 [Link]
Enhancing Sequential Recommendations through Multi-Perspective Reflections and Iteration Arxiv 2024 [Link]
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM Arxiv 2024 [Link]
Multilingual Prompts in LLM-Based Recommenders: Performance Across Languages Arxiv 2024 [Link]
Unleash LLMs Potential for Recommendation by Coordinating Twin-Tower Dynamic Semantic Token Generator Arxiv 2024 [Link]
Large Language Model Enhanced Hard Sample Identification for Denoising Recommendation Arxiv 2024 [Link]
Chain-of-thought prompting empowered generative user modeling for personalized recommendation Neural Computing and Applications [Link]
Challenging Fairness: A Comprehensive Exploration of Bias in LLM-Based Recommendations Arxiv 2024 [Link]
Decoding Style: Efficient Fine-Tuning of LLMs for Image-Guided Outfit Recommendation with Preference CIKM 2024 [Link]
LLM-Powered Text Simulation Attack Against ID-Free Recommender Systems Arxiv 2024 [Link]
FLARE: Fusing Language Models and Collaborative Architectures for Recommender Enhancement Arxiv 2024 [Link]
Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval Evaluation Arxiv 2024 [Link]
HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling Arxiv 2024 [Link]
Large Language Model Ranker with Graph Reasoning for Zero-Shot Recommendation ICANN 2024 [Link]
User Knowledge Prompt for Sequential Recommendation RecSys 2024 [Link]
RLRF4Rec: Reinforcement Learning from Recsys Feedback for Enhanced Recommendation Reranking Arxiv 2024 [Link]
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services Arxiv 2024 [Link]
TLRec: A Transfer Learning Framework to Enhance Large Language Models for Sequential Recommendation Tasks RecSys 2024 [Link]
SeCor: Aligning Semantic and Collaborative Representations by Large Language Models for Next-Point-of-Interest Recommendations RecSys 2024 [Link]
Efficient Inference for Large Language Model-based Generative Recommendation Arxiv 2024 [Link]
Instructing and Prompting Large Language Models for Explainable Cross-domain Recommendations RecSys 2024 [Link]
ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool RecSys 2024 [Link]
Inductive Generative Recommendation via Retrieval-based Speculation Arxiv 2024 [Link]

2. Datasets & Benchmarks

The datasets & benchmarks for LLM-related RS topics should maintain the original semantic/textual features, instead of anonymous feature IDs.

2.1 Datasets

Dataset RS Scenario Link
NineRec 9 Domains [Link]
MicroLens Video Streaming [Link]
Amazon-Review 2023 E-commerce [Link]
Reddit-Movie Conversational & Movie [Link]
Amazon-M2 E-commerce [Link]
MovieLens Movie [Link]
Amazon E-commerce [Link]
BookCrossing Book [Link]
GoodReads Book [Link]
Anime Anime [Link]
PixelRec Short Video [Link]
Netflix Movie [Link]

2.2 Benchmarks

Benchmarks Webcite Link Paper
Amazon-M2 (KDD Cup 2023) [Link] [Paper]
LLMRec [Link] [Paper]
OpenP5 [Link] [Paper]
TABLET [Link] [Paper]

3. Related Repositories

Repo Name Maintainer
rs-llm-paper-list wwliu555
awesome-recommend-system-pretraining-papers archersama
LLM4Rec WLiK
Awesome-LLM4RS-Papers nancheng58
LLM4IR-Survey RUC-NLPIR

Contributing

👍 Welcome to contribute to this repository.

If you have come across relevant resources or found some errors in this repesitory, feel free to open an issue or submit a pull request.

Contact: chiangel [DOT] ljh [AT] gmail [DOT] com

Citation

@article{10.1145/3678004,
author = {Lin, Jianghao and Dai, Xinyi and Xi, Yunjia and Liu, Weiwen and Chen, Bo and Zhang, Hao and Liu, Yong and Wu, Chuhan and Li, Xiangyang and Zhu, Chenxu and Guo, Huifeng and Yu, Yong and Tang, Ruiming and Zhang, Weinan},
title = {How Can Recommender Systems Benefit from Large Language Models: A Survey},
year = {2024},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issn = {1046-8188},
url = {https://doi.org/10.1145/3678004},
doi = {10.1145/3678004},
journal = {ACM Trans. Inf. Syst.},
month = {jul}
}

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yudao-boot-mini Screenshot
yudao-boot-mini

yudao-boot-mini is an open-source project focused on developing a rapid development platform for developers in China. It includes features like system functions, infrastructure, member center, data reports, workflow, mall system, WeChat official account, CRM, ERP, etc. The project is based on Spring Boot with Java backend and Vue for frontend. It offers various functionalities such as user management, role management, menu management, department management, workflow management, payment system, code generation, API documentation, database documentation, file service, WebSocket integration, message queue, Java monitoring, and more. The project is licensed under the MIT License, allowing both individuals and enterprises to use it freely without restrictions.

github
: 54
ruoyi-vue-pro Screenshot
ruoyi-vue-pro

The ruoyi-vue-pro repository is an open-source project that provides a comprehensive development platform with various functionalities such as system features, infrastructure, member center, data reports, workflow, payment system, mall system, ERP system, CRM system, and AI big model. It is built using Java backend with Spring Boot framework and Vue frontend with different versions like Vue3 with element-plus, Vue3 with vben(ant-design-vue), and Vue2 with element-ui. The project aims to offer a fast development platform for developers and enterprises, supporting features like dynamic menu loading, button-level access control, SaaS multi-tenancy, code generator, real-time communication, integration with third-party services like WeChat, Alipay, and cloud services, and more.

github
: 27.1k
yudao-cloud Screenshot
yudao-cloud

Yudao-cloud is an open-source project designed to provide a fast development platform for developers in China. It includes various system functions, infrastructure, member center, data reports, workflow, mall system, WeChat public account, CRM, ERP, etc. The project is based on Java backend with Spring Boot and Spring Cloud Alibaba microservices architecture. It supports multiple databases, message queues, authentication systems, dynamic menu loading, SaaS multi-tenant system, code generator, real-time communication, integration with third-party services like WeChat, Alipay, and more. The project is well-documented and follows the Alibaba Java development guidelines, ensuring clean code and architecture.

github
: 16.2k
gpupixel Screenshot
gpupixel

GPUPixel is a real-time, high-performance image and video filter library written in C++11 and based on OpenGL/ES. It incorporates a built-in beauty face filter that achieves commercial-grade beauty effects. The library is extremely easy to compile and integrate with a small size, supporting platforms including iOS, Android, Mac, Windows, and Linux. GPUPixel provides various filters like skin smoothing, whitening, face slimming, big eyes, lipstick, and blush. It supports input formats like YUV420P, RGBA, JPEG, PNG, and output formats like RGBA and YUV420P. The library's performance on devices like iPhone and Android is optimized, with low CPU usage and fast processing times. GPUPixel's lib size is compact, making it suitable for mobile and desktop applications.

github
: 1.2k
2020-12th-ironman Screenshot
2020-12th-ironman

This repository contains tutorial content for the 12th iT Help Ironman competition, focusing on machine learning algorithms and their practical applications. The tutorials cover topics such as AI model integration, API server deployment techniques, and hands-on programming exercises. The series is presented in video format and will be compiled into an e-book in the future. Suitable for those familiar with Python, interested in implementing AI prediction models, data analysis, and backend integration and deployment of AI models.

github
: 199
Awesome-LLM-Tabular Screenshot
Awesome-LLM-Tabular

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

github
: 250
LLamaTuner Screenshot
LLamaTuner

LLamaTuner is a repository for the Efficient Finetuning of Quantized LLMs project, focusing on building and sharing instruction-following Chinese baichuan-7b/LLaMA/Pythia/GLM model tuning methods. The project enables training on a single Nvidia RTX-2080TI and RTX-3090 for multi-round chatbot training. It utilizes bitsandbytes for quantization and is integrated with Huggingface's PEFT and transformers libraries. The repository supports various models, training approaches, and datasets for supervised fine-tuning, LoRA, QLoRA, and more. It also provides tools for data preprocessing and offers models in the Hugging Face model hub for inference and finetuning. The project is licensed under Apache 2.0 and acknowledges contributions from various open-source contributors.

github
: 545
yudao-ui-admin-vue3 Screenshot
yudao-ui-admin-vue3

The yudao-ui-admin-vue3 repository is an open-source project focused on building a fast development platform for developers in China. It utilizes Vue3 and Element Plus to provide features such as configurable themes, internationalization, dynamic route permission generation, common component encapsulation, and rich examples. The project supports the latest front-end technologies like Vue3 and Vite4, and also includes tools like TypeScript, pinia, vueuse, vue-i18n, vue-router, unocss, iconify, and wangeditor. It offers a range of development tools and features for system functions, infrastructure, workflow management, payment systems, member centers, data reporting, e-commerce systems, WeChat public accounts, ERP systems, and CRM systems.

github
: 1.6k
Chinese-LLaMA-Alpaca-2 Screenshot
Chinese-LLaMA-Alpaca-2

Chinese-LLaMA-Alpaca-2 is a large Chinese language model developed by Meta AI. It is based on the Llama-2 model and has been further trained on a large dataset of Chinese text. Chinese-LLaMA-Alpaca-2 can be used for a variety of natural language processing tasks, including text generation, question answering, and machine translation. Here are some of the key features of Chinese-LLaMA-Alpaca-2: * It is the largest Chinese language model ever trained, with 13 billion parameters. * It is trained on a massive dataset of Chinese text, including books, news articles, and social media posts. * It can be used for a variety of natural language processing tasks, including text generation, question answering, and machine translation. * It is open-source and available for anyone to use. Chinese-LLaMA-Alpaca-2 is a powerful tool that can be used to improve the performance of a wide range of natural language processing tasks. It is a valuable resource for researchers and developers working in the field of artificial intelligence.

github
: 6.8k
Chinese-LLaMA-Alpaca Screenshot
Chinese-LLaMA-Alpaca

This project open sources the **Chinese LLaMA model and the Alpaca large model fine-tuned with instructions**, to further promote the open research of large models in the Chinese NLP community. These models **extend the Chinese vocabulary based on the original LLaMA** and use Chinese data for secondary pre-training, further enhancing the basic Chinese semantic understanding ability. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, significantly improving the model's understanding and execution of instructions.

github
: 17.2k
awesome-pretrained-chinese-nlp-models Screenshot
awesome-pretrained-chinese-nlp-models

github
: 4.7k

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