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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.

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

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

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

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

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

1. Papers

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

<img width="650" src="https://github.com/CHIANGEL/Awesome-LLM-for-RecSys/blob/main/where-framework-1.png"> <details><summary><b>1.1 LLM for Feature Engineering</b></summary> <p>

<b>1.1.1 User- and Item-level Feature Augmentation</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
LLM4KGCKnowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMsPaLM (540B)/ ChatGPTFrozenArxiv 2023[Link]
TagGPTTagGPT: Large Language Models are Zero-shot Multimodal TaggersChatGPTFrozenArxiv 2023[Link]
ICPCLarge Language Models for User Interest JourneysLaMDA (137B)Full Finetuning/ Prompt TuningArxiv 2023[Link]
KARTowards Open-World Recommendation with Knowledge Augmentation from Large Language ModelsChatGPTFrozenArxiv 2023[Link]
PIEProduct Information Extraction using ChatGPTChatGPTFrozenArxiv 2023[Link]
LGIREnhancing Job Recommendation through LLM-based Generative Adversarial NetworksGhatGLM (6B)FrozenAAAI 2024[Link]
GIRLGenerative Job Recommendations with Large Language ModelBELLE (7B)Full FinetuningArxiv 2023[Link]
LLM-RecLLM-Rec: Personalized Recommendation via Prompting Large Language Modelstext-davinci-003FrozenArxiv 2023[Link]
HKFRHeterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLMChatGPTFrozenRecSys 2023[Link]
LLaMA-ELLaMA-E: Empowering E-commerce Authoring with Multi-Aspect Instruction FollowingLLaMA (30B)LoRAArxiv 2023[Link]
EcomGPTEcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerceBLOOMZ (7.1B)Full FinetuningArxiv 2023[Link]
TF-DConLeveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based RecommendationChatGPTFrozenArxiv 2023[Link]
RLMRecRepresentation Learning with Large Language Models for RecommendationChatGPTFrozenWWW 2024[Link]
LLMRecLLMRec: Large Language Models with Graph Augmentation for RecommendationChatGPTFrozenWSDM 2024[Link]
LLMRGEnhancing Recommender Systems with Large Language Model Reasoning GraphsGPT4FrozenArxiv 2023[Link]
CUPRecommendations by Concise User Profiles from Review TextChatGPTFrozenArxiv 2023[Link]
SINGLEModeling User Viewing Flow using Large Language Models for Article RecommendationChatGPTFrozenArxiv 2023[Link]
SAGCNUnderstanding Before Recommendation: Semantic Aspect-Aware Review Exploitation via Large Language ModelsVicuna (13B)FrozenArxiv 2023[Link]
UEMUser Embedding Model for Personalized Language PromptingFLAN-T5-base (250M)Full FinetuningArxiv 2024[Link]
LLMHGLLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable RecommendationGPT4FrozenArxiv 2024[Link]
Llama4RecIntegrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive AggregationLLaMA2 (7B)Full FinetuningArxiv 2024[Link]
LLM4VisLLM4Vis: Explainable Visualization Recommendation using ChatGPTChatGPTFrozenEMNLP 2023[Link]
LoRecLoRec: Large Language Model for Robust Sequential Recommendation against Poisoning AttacksLLaMA2FrozenSIGIR 2024[Link]

<b>1.1.2 Instance-level Sample Generation</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
GReaTLanguage Models are Realistic Tabular Data GeneratorsGPT2-medium (355M)Full FinetuningICLR 2023[Link]
ONCEONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language ModelsChatGPTFrozenWSDM 2024[Link]
AnyPredictAnyPredict: Foundation Model for Tabular PredictionChatGPTFrozenArxiv 2023[Link]
DPLLMPrivacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language ModelsT5-XL (3B)Full FinetuningArxiv 2023[Link]
MINTLarge Language Model Augmented Narrative Driven Recommendationstext-davinci-003FrozenRecSys 2023[Link]
Agent4RecOn Generative Agents in RecommendationChatGPTFrozenArxiv 2023[Link]
RecPromptRecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language ModelsGPT4FrozenArxiv 2023[Link]
PO4ISRLarge Language Models for Intent-Driven Session RecommendationsChatGPTFrozenArxiv 2023[Link]
BEQUELarge Language Model based Long-tail Query Rewriting in Taobao SearchChatGLM (6B)FFTArxiv 2023[Link]
Agent4RankingAgent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLMChatGPTFrozenArxiv 2023[Link]
PopNudgeImproving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data AugmentationChatGPTFrozenArxiv 2023[Link]
</p> </details> <details><summary><b>1.2 LLM as Feature Encoder</b></summary> <p>

<b>1.2.1 Representation Enhancement</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
U-BERTU-BERT: Pre-training User Representations for Improved RecommendationBERT-base (110M)Full FinetuningAAAI 2021[Link]
UNBERTUNBERT: User-News Matching BERT for News RecommendationBERT-base (110M)Full FinetuningIJCAI 2021[Link]
PLM-NREmpowering News Recommendation with Pre-trained Language ModelsRoBERTa-base (125M)Full FinetuningSIGIR 2021[Link]
Pyramid-ERNIEPre-trained Language Model based Ranking in Baidu SearchERNIE (110M)Full FinetuningKDD 2021[Link]
ERNIE-RSPre-trained Language Model for Web-scale Retrieval in Baidu SearchERNIE (110M)Full FinetuningKDD 2021[Link]
CTR-BERTCTR-BERT: Cost-effective knowledge distillation for billion-parameter teacher modelsCustomized BERT (1.5B)Full FinetuningENLSP 2021[Link]
SuKDLearning Supplementary NLP Features for CTR Prediction in Sponsored SearchRoBERTa-large (355M)Full FinetuningKDD 2022[Link]
PRECBoosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News RecommendationBERT-base (110M)Full FinetuningCOLING 2022[Link]
MM-RecMM-Rec: Visiolinguistic Model Empowered Multimodal News RecommendationBERT-base (110M)Full FinetuningSIGIR 2022[Link]
Tiny-NewsRecTiny-NewsRec: Effective and Efficient PLM-based News RecommendationUniLMv2-base (110M)Full FinetuningEMNLP 2022[Link]
PLM4TagPTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained ModelsCodeBERT (125M)Full FinetuningICPC 2022[Link]
TwHIN-BERTTwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet RepresentationsBERT-base (110M)Full FinetuningArxiv 2022[Link]
LSHImproving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative StudyBERT-base (110M)Full FinetuningArxiv 2023[Link]
LLM2BERT4RecLeveraging Large Language Models for Sequential Recommendationtext-embedding-ada-002FrozenRecSys 2023[Link]
LLM4ARecPrompt Tuning Large Language Models on Personalized Aspect Extraction for RecommendationsGPT2 (110M)Prompt TuningArxiv 2023[Link]
TIGERRecommender Systems with Generative RetrievalSentence-T5-base (223M)FrozenNIPS 2023[Link]
TBINTBIN: Modeling Long Textual Behavior Data for CTR PredictionBERT-base (110M)FrozenDLP-RecSys 2023[Link]
LKPNRLKPNR: LLM and KG for Personalized News Recommendation FrameworkLLaMA2 (7B)FrozenArxiv 2023[Link]
SSNATowards Efficient and Effective Adaptation of Large Language Models for Sequential RecommendationDistilRoBERTa-base (83M)Layerwise Adapter TuningArxiv 2023[Link]
CollabContextCollaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language ModelInstructor-XL (1.5B)FrozenArxiv 2023[Link]
LMIndexerLanguage Models As Semantic IndexersT5-base (223M)Full FinetuningArxiv 2023[Link]
StackA BERT based Ensemble Approach for Sentiment Classification of Customer Reviews and its Application to Nudge Marketing in e-CommerceBERT-base (110M)FrozenArxiv 2023[Link]
N/AUtilizing Language Models for Tour Itinerary RecommendationBERT-base (110M)Full FinetuningPMAI@IJCAI 2023[Link]
UEMUser Embedding Model for Personalized Language PromptingSentence-T5-base (223M)FrozenArxiv 2024[Link]
Social-LLMSocial-LLM: Modeling User Behavior at Scale using Language Models and Social Network DataSBERT-MPNet-base (110M)FrozenArxiv 2024[Link]
LLMRSLLMRS: Unlocking Potentials of LLM-Based Recommender Systems for Software PurchaseMPNet (110M)FrozenArxiv 2024[Link]
KERLKnowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender SystemsBERT-miniFrozenTNNLS[Link]
N/AEmpowering Few-Shot Recommender Systems with Large Language Models -- Enhanced RepresentationsChatGPTFrozenIEEE Access[Link]
N/ABetter Generalization with Semantic IDs: A Case Study in Ranking for RecommendationsUnknownFrozenArxiv 2023[Link]

<b>1.2.2 Unified Cross-domain Recommendation</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
ZESRecZero-Shot Recommender SystemsBERT-base (110M)FrozenArxiv 2021[Link]
UniSRecTowards Universal Sequence Representation Learning for Recommender SystemsBERT-base (110M)FrozenKDD 2022[Link]
TransRecTransRec: Learning Transferable Recommendation from Mixture-of-Modality FeedbackBERT-base (110M)Full FinetuningArxiv 2022[Link]
VQ-RecLearning Vector-Quantized Item Representation for Transferable Sequential RecommendersBERT-base (110M)FrozenWWW 2023[Link]
IDRec vs MoRecWhere to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models RevisitedBERT-base (110M)Full FinetuningSIGIR 2023[Link]
TransRecExploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical InsightsRoBERTa-base (125M)Layerwise Adapter TuningArxiv 2023[Link]
TCFExploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and InsightsOPT-175B (175B)Frozen/ Full FinetuningArxiv 2023[Link]
S&R FoundationAn Unified Search and Recommendation Foundation Model for Cold-Start ScenarioChatGLM (6B)FrozenCIKM 2023[Link]
MISSRecMISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for RecommendationCLIP-B/32 (400M)Full FinetuningMM 2023[Link]
UFINUFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate PredictionFLAN-T5-base (250M)FrozenArxiv 2023[Link]
PMMRecMulti-Modality is All You Need for Transferable Recommender SystemsRoBERTa-large (355M)Top-2-layer FinetuningICDE 2024[Link]
Uni-CTRA Unified Framework for Multi-Domain CTR Prediction via Large Language ModelsSheared-LLaMA (1.3B)LoRAArxiv 2023[Link]
PCDRPrompt-enhanced Federated Content Representation Learning for Cross-domain RecommendationBERT-base (110M)FrozenWWW 2024[Link]
</p> </details> <details><summary><b>1.3 LLM as Scoring/Ranking Function</b></summary> <p>

<b>1.3.1 Item Scoring Task</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
LMRecSysLanguage Models as Recommender Systems: Evaluations and LimitationsGPT2-XL (1.5B)Full FinetuningICBINB 2021[Link]
PTabPTab: Using the Pre-trained Language Model for Modeling Tabular DataBERT-base (110M)Full FinetuningArxiv 2022[Link]
UniTRecUniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based RecommendationBART (406M)Full FinetuningACL 2023[Link]
Prompt4NRPrompt Learning for News RecommendationBERT-base (110M)Full FinetuningSIGIR 2023[Link]
RecFormerText Is All You Need: Learning Language Representations for Sequential RecommendationLongFormer (149M)Full FinetuningKDD 2023[Link]
TabLLMTabLLM: Few-shot Classification of Tabular Data with Large Language ModelsT0 (11B)Few-shot Parameter-effiecnt FinetuningAISTATS 2023[Link]
Zero-shot GPTZero-Shot Recommendation as Language ModelingGPT2-medium (355M)FrozenArxiv 2023[Link]
FLAN-T5Do LLMs Understand User Preferences? Evaluating LLMs On User Rating PredictionFLAN-5-XXL (11B)Full FinetuningArxiv 2023[Link]
BookGPTBookGPT: A General Framework for Book Recommendation Empowered by Large Language ModelChatGPTFrozenArxiv 2023[Link]
TALLRecTALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with RecommendationLLaMA (7B)LoRARecSys 2023[Link]
PBNRPBNR: Prompt-based News Recommender SystemT5-small (60M)Full FinetuningArxiv 2023[Link]
CR-SoRecCR-SoRec: BERT driven Consistency Regularization for Social RecommendationBERT-base (110M)Full FinetuningRecSys 2023[Link]
PromptRecTowards Personalized Cold-Start Recommendation with PromptsLLaMA (7B)FrozenArxiv 2023[Link]
GLRecExploring Large Language Model for Graph Data Understanding in Online Job RecommendationsBELLE-LLaMA (7B)LoRAArxiv 2023[Link]
BERT4CTRBERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR PredictionRoBERTa-large (355M)Full FinetuningKDD 2023[Link]
ReLLaReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in RecommendationVicuna (13B)LoRAWWW 2024[Link]
TASTEText Matching Improves Sequential Recommendation by Reducing Popularity BiasesT5-base (223M)Full FinetuningCIKM 2023[Link]
N/AUnveiling Challenging Cases in Text-based Recommender SystemsBERT-base (110M)Full FinetuningRecSys Workshop 2023[Link]
ClickPromptClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR PredictionRoBERTa-large (355M)Full FinetuningWWW 2024[Link]
SetwiseRankA Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language ModelsFLAN-T5-XXL (11B)FrozenArxiv 2023[Link]
UPSRThoroughly Modeling Multi-domain Pre-trained Recommendation as LanguageT5-base (223M)Full FinetuningArxiv 2023[Link]
LLM-RecOne Model for All: Large Language Models are Domain-Agnostic Recommendation SystemsOPT (6.7B)LoRAArxiv 2023[Link]
LLMRankerBeyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance LabelsFLAN PaLM2 SFrozenArxiv 2023[Link]
CoLLMCoLLM: Integrating Collaborative Embeddings into Large Language Models for RecommendationVicuna (7B)LoRAArxiv 2023[Link]
FLIPFLIP: Towards Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR PredictionRoBERTa-large (355M)Full FinetuningArxiv 2023[Link]
BTRecBTRec: BERT-Based Trajectory Recommendation for Personalized ToursBERT-base (110M)Full FinetuningArxiv 2023[Link]
CLLM4RecCollaborative Large Language Model for Recommender SystemsGPT2 (110M)Full FinetuningArxiv 2023[Link]
CUPRecommendations by Concise User Profiles from Review TextBERT-base (110M)Last-layer FinetuningArxiv 2023[Link]
N/AInstruction Distillation Makes Large Language Models Efficient Zero-shot RankersFLAN-T5-XL (3B)Full FinetuningArxiv 2023[Link]
CoWPiRecCollaborative Word-based Pre-trained Item Representation for Transferable RecommendationBERT-base (110M)Full FinetuningICDM 2023[Link]
RecExplainerRecExplainer: Aligning Large Language Models for Recommendation Model InterpretabilityVicuna-v1.3 (7B)LoRAArxiv 2023[Link]
E4SRecE4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential RecommendationLLaMA2 (13B)LoRAArxiv 2023[Link]
CERThe Problem of Coherence in Natural Language Explanations of RecommendationsGPT2 (110M)Full FinetuningECAI 2023[Link]
LSATPreliminary Study on Incremental Learning for Large Language Model-based Recommender SystemsLLaMA (7B)LoRAArxiv 2023[Link]
Llama4RecIntegrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive AggregationLLaMA2 (7B)Full FinetuningArxiv 2024[Link]

<b>1.3.2 Item Generation Task</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
GPT4RecGPT4Rec: A Generative Framework for Personalized Recommendation and User Interests InterpretationGPT2 (110M)Full FinetuningArxiv 2023[Link]
VIP5VIP5: Towards Multimodal Foundation Models for RecommendationT5-base (223M)Layerwise Adater TuningEMNLP 2023[Link]
P5-IDHow to Index Item IDs for Recommendation Foundation ModelsT5-small (60M)Full FinetuningArxiv 2023[Link]
FaiRLLMIs ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model RecommendationChatGPTFrozenRecSys 2023[Link]
PALRPALR: Personalization Aware LLMs for RecommendationLLaMA (7B)Full FinetuningArxiv 2023[Link]
ChatGPTLarge Language Models are Zero-Shot Rankers for Recommender SystemsChatGPTFrozenECIR 2024[Link]
AGRSparks of Artificial General Recommender (AGR): Early Experiments with ChatGPTChatGPTFrozenArxiv 2023[Link]
NIRZero-Shot Next-Item Recommendation using Large Pretrained Language ModelsGPT3 (175B)FrozenArxiv 2023[Link]
GPTRecGenerative Sequential Recommendation with GPTRecGPT2-medium (355M)Full FinetuningGen-IR@SIGIR 2023[Link]
ChatNewsA Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake NewsChatGPTFrozenArxiv 2023[Link]
N/ALarge Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based PreferencesPaLM (62B)FrozenRecSys 2023[Link]
LLMSeqPromptLeveraging Large Language Models for Sequential RecommendationOpenAI ada modelFinetuneRecSys 2023[Link]
GenRecGenRec: Large Language Model for Generative RecommendationLLaMA (7B)LoRAArxiv 2023[Link]
UP5UP5: Unbiased Foundation Model for Fairness-aware RecommendationT5-base (223M)Prefix TuningArxiv 2023[Link]
HKFRHeterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLMChatGLM (6B)LoRARecSys 2023[Link]
N/AThe Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job RecommendationsChatGPTFrozenEAAMO 2023[Link]
BIGRecA Bi-Step Grounding Paradigm for Large Language Models in Recommendation SystemsLLaMA (7B)LoRAArxiv 2023[Link]
KP4SRKnowledge Prompt-tuning for Sequential RecommendationT5-small (60M)Full FinetuningArxiv 2023[Link]
RecSysLLMLeveraging Large Language Models for Pre-trained Recommender SystemsGLM (10B)LoRAArxiv 2023[Link]
PODPrompt Distillation for Efficient LLM-based RecommendationT5-small (60M)Full FinetuningCIKM 2023[Link]
N/AEvaluating ChatGPT as a Recommender System: A Rigorous ApproachChatGPTFrozenArxiv 2023[Link]
RaRSRetrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language ModelsChatGPTFrozenRecSys Doctoral Symposium 2023[Link]
JobRecoGPTJobRecoGPT -- Explainable job recommendations using LLMsGPT4FrozenArxiv 2023[Link]
LANCERReformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language ModelingGPT2 (110M)Prefix TuningArxiv 2023[Link]
TransRecA Multi-facet Paradigm to Bridge Large Language Model and RecommendationLLaMA (7B)LoRAArxiv 2023[Link]
AgentCFAgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systemstext-davinci-003 & gpt-3.5-turboFrozenWWW 2024[Link]
P4LMFactual and Personalized Recommendations using Language Models and Reinforcement LearningPaLM2-XSFull FinetuningArxiv 2023[Link]
InstructMKMultiple Key-value Strategy in Recommendation Systems Incorporating Large Language ModelLLaMA (7B)Full FinetuningCIKM GenRec 2023[Link]
LightLMLightLM: A Lightweight Deep and Narrow Language Model for Generative RecommendationT5-small (60M)Full FinetuningArxiv 2023[Link]
LlamaRecLlamaRec: Two-Stage Recommendation using Large Language Models for RankingLLaMA2 (7B)QLoRAPGAI@CIKM 2023[Link]
N/AExploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case StudyGPT-4VFrozenArxiv 2023[Link]
N/AExploring Fine-tuning ChatGPT for News RecommendationChatGPTgpt-3.5-turbo finetuning APIArxiv 2023[Link]
N/ADo LLMs Implicitly Exhibit User Discrimination in Recommendation? An Empirical StudyChatGPTFrozenArxiv 2023[Link]
LC-RecAdapting Large Language Models by Integrating Collaborative Semantics for RecommendationLLaMA (7B)LoRAArxiv 2023[Link]
DOKEKnowledge Plugins: Enhancing Large Language Models for Domain-Specific RecommendationsChatGPTFrozenArxiv 2023[Link]
ControlRecControlRec: Bridging the Semantic Gap between Language Model and Personalized RecommendationT5-base (223M)Full FinetuningArxiv 2023[Link]
LLaRALLaRA: Large Language-Recommendation AssistantLLaMA2 (7B)LoRASIGIR 2024[Link]
PO4ISRLarge Language Models for Intent-Driven Session RecommendationsChatGPTFrozenArxiv 2023[Link]
DRDTDRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential RecommendationChatGPTFrozenArxiv 2023[Link]
RecPromptRecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language ModelsGPT4FrozenArxiv 2023[Link]
LiT5Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder ModelsT5-XL (3B)Full FinetuningArxiv 2023[Link]
STELLALarge Language Models are Not Stable Recommender SystemsChatGPTFrozenArxiv 2023[Link]
Llama4RecIntegrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive AggregationLLaMA2 (7B)Full FinetuningArxiv 2024[Link]
RECLLMUnderstanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and RecencyChatGPTFrozenArxiv 2024[Link]
DEALRecData-efficient Fine-tuning for LLM-based RecommendationLLaMA (7B)LoRAArxiv 2024[Link]

<b>1.3.3 Hybrid Task</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
P5Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)T5-base (223M)Full FinetuningRecSys 2022[Link]
M6-RecM6-Rec: Generative Pretrained Language Models are Open-Ended Recommender SystemsM6-base (300M)Option TuningArxiv 2022[Link]
InstructRecRecommendation as Instruction Following: A Large Language Model Empowered Recommendation ApproachFLAN-T5-XL (3B)Full FinetuningArxiv 2023[Link]
ChatGPTIs ChatGPT a Good Recommender? A Preliminary StudyChatGPTFrozenArxiv 2023[Link]
ChatGPTIs ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking AgentChatGPTFrozenArxiv 2023[Link]
ChatGPTUncovering ChatGPT's Capabilities in Recommender SystemsChatGPTFrozenRecSys 2023[Link]
BDLMBridging the Information Gap Between Domain-Specific Model and General LLM for Personalized RecommendationVicuna (7B)Full FinetuningArxiv 2023[Link]
RecRankerRecRanker: Instruction Tuning Large Language Model as Ranker for Top-k RecommendationLLaMA2 (13B)Full FinetuningArxiv 2023[Link]
</p> </details> <details><summary><b>1.4 LLM for User Interaction</b></summary> <p>

<b>1.4.1 Task-oriented User Interaction</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
TG-ReDialTowards Topic-Guided Conversational Recommender SystemBERT-base (110M) & GPT2 (110M)UnknownCOLING 2020[Link]
TCPFollow Me: Conversation Planning for Target-driven Recommendation Dialogue SystemsBERT-base (110M)Full FinetuningArxiv 2022[Link]
MESEImproving Conversational Recommendation Systems' Quality with Context-Aware Item Meta-InformationDistilBERT (67M) & GPT2 (110M)Full FinetuningACL 2022[Link]
UniMINDA Unified Multi-task Learning Framework for Multi-goal Conversational Recommender SystemsBART-base (139M)Full FinetuningACM TOIS 2023[Link]
VRICRVariational Reasoning over Incomplete Knowledge Graphs for Conversational RecommendationBERT-base (110M)Full FinetuningWSDM 2023[Link]
KECRExplicit Knowledge Graph Reasoning for Conversational RecommendationBERT-base (110M) & GPT2 (110M)FrozenACM TIST 2023[Link]
N/ALarge Language Models as Zero-Shot Conversational RecommendersGPT4FrozenCIKM 2023[Link]
MuseChatMuseChat: A Conversational Music Recommendation System for VideosVicuna (7B)LoRAArxiv 2023[Link]
N/AConversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales DialogueChinese-Alpaca (7B)LoRAEMNLP 2023 Findings[Link]
N/AChatGPT for Conversational Recommendation: Refining Recommendations by Reprompting with FeedbackChatGPTFrozenArxiv 2024[Link]

<b>1.4.2 Open-ended User Interaction</b>

NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
BARCORBARCOR: Towards A Unified Framework for Conversational Recommendation SystemsBART-base (139M)Selective-layer FinetuningArxiv 2022[Link]
RecInDialRecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language ModelsDialoGPT (110M)Full FinetuningAACL 2022[Link]
UniCRSTowards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt LearningDialoGPT-small (176M)FrozenKDD 2022[Link]
T5-CRMulti-Task End-to-End Training Improves Conversational RecommendationT5-base (223M)Full FinetuningArxiv 2023[Link]
TtWTalk the Walk: Synthetic Data Generation for Conversational Music RecommendationT5-base (223M) & T5-XXL (11B)Full Finetuning & FrozenArxiv 2023[Link]
N/ARethinking the Evaluation for Conversational Recommendation in the Era of Large Language ModelsChatGPTFrozenEMNLP 2023[Link]
PECRSParameter-Efficient Conversational Recommender System as a Language Processing TaskGPT2-medium (355M)LoRAEACL 2024[Link]
</p> </details> <details><summary><b>1.5 LLM for RS Pipeline Controller</b></summary> <p>
NamePaperLLM Backbone (Largest)LLM Tuning StrategyPublicationLink
Chat-RECChat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender SystemChatGPTFrozenArxiv 2023[Link]
RecLLMLeveraging Large Language Models in Conversational Recommender SystemsLLaMA (7B)Full FinetuningArxiv 2023[Link]
RAHRAH! RecSys-Assistant-Human: A Human-Central Recommendation Framework with Large Language ModelsGPT4FrozenArxiv 2023[Link]
RecMindRecMind: Large Language Model Powered Agent For RecommendationChatGPTFrozenNAACL 2024[Link]
InteRecAgentRecommender AI Agent: Integrating Large Language Models for Interactive RecommendationsGPT4FrozenArxiv 2023[Link]
CORELending Interaction Wings to Recommender Systems with Conversational AgentsN/AN/ANIPS 2023[Link]
LLMCRSA Large Language Model Enhanced Conversational Recommender SystemLLaMA (7B)Full FinetuningArxiv 2023[Link]
</p> </details> <details><summary><b>1.6 Related Survey Papers</b></summary> <p>
PaperPublicationLink
Large Language Model Enhanced Recommender Systems: Taxonomy, Trend, Application and FutureArxiv 2024[Link]
Recommender Systems in the Era of Large Language Model Agents: A SurveyPreprint[Link]
A Survey on Efficient Solutions of Large Language Models for RecommendationArxiv 2024[Link]
Towards Next-Generation LLM-based Recommender Systems: A Survey and BeyondArxiv 2024[Link]
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM EraKDD 2024[Link]
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM EraArxiv 2024[Link]
Survey for Landing Generative AI in Social and E-commerce Recsys - the Industry PerspectivesArxiv 2024[Link]
A Survey of Generative Search and Recommendation in the Era of Large Language ModelsArxiv 2024[Link]
When Search Engine Services meet Large Language Models: Visions and ChallengesArxiv 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 ReviewArxiv 2024[Link]
Foundation Models for Recommender Systems: A Survey and New PerspectivesArxiv 2024[Link]
Prompting Large Language Models for Recommender Systems: A Comprehensive Framework and Empirical AnalysisArixv 2024[Link]
User Modeling in the Era of Large Language Models: Current Research and Future DirectionsIEEE Data Engineering Bulletin 2023[Link]
A Survey on Large Language Models for Personalized and Explainable RecommendationsArxiv 2023[Link]
Large Language Models for Generative Recommendation: A Survey and Visionary DiscussionsArxiv 2023[Link]
Large Language Models for Information Retrieval: A SurveyArxiv 2023[Link]
When Large Language Models Meet Personalization: Perspectives of Challenges and OpportunitiesArxiv 2023[Link]
Recommender Systems in the Era of Large Language Models (LLMs)Arxiv 2023[Link]
A Survey on Large Language Models for RecommendationArxiv 2023[Link]
Pre-train, Prompt and Recommendation: A Comprehensive Survey of Language Modelling Paradigm Adaptations in Recommender SystemsTACL 2023[Link]
Self-Supervised Learning for Recommender Systems: A SurveyTKDE 2022[Link]
</p> </details> <details><summary><b>1.7 Newest Research Work List</b></summary> <p>
PaperPublicationLink
Large Language Model Can Interpret Latent Space of Sequential RecommenderArxiv 2023[Link]
Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal NudgingArxiv 2023[Link]
INTERS: Unlocking the Power of Large Language Models in Search with Instruction TuningArxiv 2024[Link]
Evaluation of Synthetic Datasets for Conversational Recommender SystemsArxiv 2023[Link]
Generative Recommendation: Towards Next-generation Recommender ParadigmArxiv 2023[Link]
Towards Personalized Prompt-Model Retrieval for Generative RecommendationArxiv 2023[Link]
Generative Next-Basket RecommendationRecSys 2023[Link]
Unlocking the Potential of Large Language Models for Explainable RecommendationsArxiv 2023[Link]
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMsFalcon (40B)Frozen
Improving Sequential Recommendations with LLMsArxiv 2024[Link]
A Multi-Agent Conversational Recommender SystemArxiv 2024[Link]
TransFR: Transferable Federated Recommendation with Pre-trained Language ModelsArxiv 2024[Link]
Large Language Model Distilling Medication Recommendation ModelArxiv 2024[Link]
Uncertainty-Aware Explainable Recommendation with Large Language ModelsArxiv 2024[Link]
Natural Language User Profiles for Transparent and Scrutable RecommendationsArxiv 2024[Link]
Leveraging LLMs for Unsupervised Dense Retriever RankingArxiv 2024[Link]
RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based RecommendationArxiv 2024[Link]
A Multi-Agent Conversational Recommender SystemArxiv 2024[Link]
Fairly Evaluating Large Language Model-based Recommendation Needs Revisit the Cross-Entropy LossArxiv 2024[Link]
SearchAgent: A Lightweight Collaborative Search Agent with Large Language ModelsArxiv 2024[Link]
Large Language Model Interaction Simulator for Cold-Start Item RecommendationArxiv 2024[Link]
Enhancing ID and Text Fusion via Alternative Training in Session-based RecommendationArxiv 2024[Link]
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction DataArxiv 2024[Link]
LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized RecommendationsArxiv 2024[Link]
LLM-based Federated RecommendationArxiv 2024[Link]
Rethinking Large Language Model Architectures for Sequential RecommendationsArxiv 2024[Link]
Large Language Model with Graph Convolution for RecommendationArxiv 2024[Link]
Rec-GPT4V: Multimodal Recommendation with Large Vision-Language ModelsArxiv 2024[Link]
Enhancing Recommendation Diversity by Re-ranking with Large Language ModelsArxiv 2024[Link]
Are ID Embeddings Necessary? Whitening Pre-trained Text Embeddings for Effective Sequential RecommendationArxiv 2024[Link]
SPAR: Personalized Content-Based Recommendation via Long Engagement AttentionArxiv 2024[Link]
Cognitive Personalized Search Integrating Large Language Models with an Efficient Memory MechanismWWW 2024[Link]
Large Language Models as Data Augmenters for Cold-Start Item RecommendationArxiv 2024[Link]
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from Large Language ModelsArxiv 2024[Link]
LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based RecommendationArxiv 2024[Link]
Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge GraphArxiv 2024[Link]
User-LLM: Efficient LLM Contextualization with User EmbeddingsArxiv 2024[Link]
Stealthy Attack on Large Language Model based RecommendationArxiv 2024[Link]
Multi-Agent Collaboration Framework for Recommender SystemsArxiv 2024[Link]
Item-side Fairness of Large Language Model-based Recommendation SystemWWW 2024[Link]
Integrating Large Language Models with Graphical Session-Based RecommendationArxiv 2024[Link]
Language-Based User Profiles for RecommendationLLM-IGS@WSDM2024[Link]
BASES: Large-scale Web Search User Simulation with Large Language Model based AgentsArxiv 2024[Link]
Prospect Personalized Recommendation on Large Language Model-based Agent PlatformArxiv 2024[Link]
Sequence-level Semantic Representation Fusion for Recommender SystemsArxiv 2024[Link]
Corpus-Steered Query Expansion with Large Language ModelsECAL 2024[Link]
NoteLLM: A Retrievable Large Language Model for Note RecommendationWWW 2024[Link]
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-CommerceWWW 2024[Link]
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value ExtractionArxiv 2024[Link]
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model PlanningArxiv 2024[Link]
InteraRec: Interactive Recommendations Using Multimodal Large Language ModelsArxiv 2024[Link]
ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented FrameworkCHASE 2024[Link]
Towards Efficient and Effective Unlearning of Large Language Models for RecommendationArxiv 2024[Link]
Generative News RecommendationWWW 2024[Link]
Bridging Language and Items for Retrieval and RecommendationArxiv 2024[Link]
Can Small Language Models be Good Reasoners for Sequential Recommendation?WWW 2024[Link]
Aligning Large Language Models for Controllable RecommendationsArxiv 2024[Link]
Personalized Audiobook Recommendations at Spotify Through Graph Neural NetworksWWW 2024[Link]
Towards Graph Foundation Models for PersonalizationArxiv 2024[Link]
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender SystemArxiv 2024[Link]
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail RecommendationArxiv 2024[Link]
RecAI: Leveraging Large Language Models for Next-Generation Recommender SystemsWWW 2024 Demo[Link]
KELLMRec: Knowledge-Enhanced Large Language Models for RecommendationArxiv 2024[Link]
USimAgent: Large Language Models for Simulating Search UsersArxiv 2024[Link]
CALRec: Contrastive Alignment of Generative LLMs For Sequential RecommendationArxiv 2024[Link]
Integrating Large Language Models with Graphical Session-Based RecommendationArxiv 2024[Link]
Language-Based User Profiles for RecommendationLLM-IGS@WSDM2024[Link]
BASES: Large-scale Web Search User Simulation with Large Language Model based AgentsArxiv 2024[Link]
Prospect Personalized Recommendation on Large Language Model-based Agent PlatformArxiv 2024[Link]
Sequence-level Semantic Representation Fusion for Recommender SystemsArxiv 2024[Link]
Corpus-Steered Query Expansion with Large Language ModelsEACL 2024[Link]
NoteLLM: A Retrievable Large Language Model for Note RecommendationWWW 2024[Link]
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-CommerceWWW 2024[Link]
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value ExtractionSIGIR 2024[Link]
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model PlanningSIGIR 2024[Link]
Towards Efficient and Effective Unlearning of Large Language Models for RecommendationFCS[Link]
Generative News RecommendationWWW 2024[Link]
Bridging Language and Items for Retrieval and RecommendationArxiv 2024[Link]
Can Small Language Models be Good Reasoners for Sequential Recommendation?WWW 2024[Link]
Aligning Large Language Models for Controllable RecommendationsArxiv 2024[Link]
Personalized Audiobook Recommendations at Spotify Through Graph Neural NetworksWWW 2024[Link]
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender SystemArxiv 2024[Link]
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail RecommendationArxiv 2024[Link]
RecAI: Leveraging Large Language Models for Next-Generation Recommender SystemsWWW 2024[Link]
KELLMRec: Knowledge-Enhanced Large Language Models for RecommendationArxiv 2024[Link]
Towards Graph Foundation Models for PersonalizationArxiv 2024[Link]
USimAgent: Large Language Models for Simulating Search UsersArxiv 2024[Link]
The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential RecommendationNAACL 2024[Link]
PPM : A Pre-trained Plug-in Model for Click-through Rate PredictionWWW 2024[Link]
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationArxiv 2024[Link]
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and BeyondICLR 2024[Link]
Harnessing Large Language Models for Text-Rich Sequential RecommendationArxiv 2024[Link]
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment RecommendationArxiv 2024[Link]
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start RecommendationsArxiv 2024[Link]
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language ModelsArxiv 2024[Link]
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action ModelingArxiv 2024[Link]
Large Language Models Enhanced Collaborative FilteringArxiv 2024[Link]
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start UsersLREC-COLING 2024[Link]
Sequential Recommendation with Latent Relations based on Large Language ModelArxiv 2024[Link]
Enhanced Generative Recommendation via Content and Collaboration IntegrationArxiv 2024[Link]
To Recommend or Not: Recommendability Identification in Conversations with Pre-trained Language ModelsArxiv 2024[Link]
IDGenRec: LLM-RecSys Alignment with Textual ID LearningSIGIR 2024[Link]
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User BehaviorsSIGIR 2024[Link]
Make Large Language Model a Better RankerArxiv 2024[Link]
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as RankersNAACL 2024[Link]
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFTSIGIR 2024[Link]
Where to Move Next: Zero-shot Generalization of LLMs for Next POI RecommendationArxiv 2024[Link]
Tired of Plugins? Large Language Models Can Be End-To-End RecommenderArxiv 2024[Link]
Aligning Large Language Models with Recommendation KnowledgeNAACL 2024[Link]
Enhancing Content-based Recommendation via Large Language ModelArxiv 2024[Link]
DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-levelArxiv 2024[Link]
Optimization Methods for Personalizing Large Language Models through Retrieval AugmentationArxiv 2024[Link]
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language ModelsArxiv 2024[Link]
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced TransformerArxiv 2024[Link]
PMG : Personalized Multimodal Generation with Large Language ModelsArxiv 2024[Link]
The Elephant in the Room: Rethinking the Usage of Pre-trained Language Model in Sequential RecommendationArxiv 2024[Link]
Exact and Efficient Unlearning for Large Language Model-based RecommendationArxiv 2024[Link]
Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender SystemArxiv 2024[Link]
Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommendation SystemsSIGIR 2024[Link]
Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM RankersArxiv 2024[Link]
RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training ParadigmArxiv 2024[Link]
MMGRec: Multimodal Generative Recommendation with Transformer ModelArxiv 2024[Link]
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce SearchArxiv 2024[Link]
Contrastive Quantization based Semantic Code for Generative RecommendationArxiv 2024[Link]
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value ExtractionArxiv 2024[Link]
Large Language Models for Next Point-of-Interest RecommendationSIGIR 2024[Link]
Ranked List Truncation for Large Language Model-based Re-RankingSIGIR 2024[Link]
Large Language Models as Conversational Movie Recommenders: A User StudyArxiv 2024[Link]
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language ModelArxiv 2024[Link]
Efficient and Responsible Adaptation of Large Language Models for Robust Top-k RecommendationsArxiv 2024[Link]
FairEvalLLM. A Comprehensive Framework for Benchmarking Fairness in Large Language Model Recommender SystemsArxiv 2024[Link]
Improve Temporal Awareness of LLMs for Sequential RecommendationArxiv 2024[Link]
CALRec: Contrastive Alignment of Generative LLMs For Sequential RecommendationArxiv 2024[Link]
Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial ApplicationArxiv 2024[Link]
DynLLM: When Large Language Models Meet Dynamic Graph RecommendationArxiv 2024[Link]
Learnable Tokenizer for LLM-based Generative RecommendationArxiv 2024[Link]
CELA: Cost-Efficient Language Model Alignment for CTR PredictionArxiv 2024[Link]
RDRec: Rationale Distillation for LLM-based RecommendationACL 2024[Link]
EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based RecommendationsArxiv 2024[Link]
Reindex-Then-Adapt: Improving Large Language Models for Conversational RecommendationArxiv 2024[Link]
RecGPT: Generative Pre-training for Text-based RecommendationACL 2024[Link]
Let Me Do It For You: Towards LLM Empowered Recommendation via Tool LearningSIGIR 2024[Link]
Finetuning Large Language Model for Personalized RankingArxiv 2024[Link]
LLMs for User Interest Exploration: A Hybrid ApproachArxiv 2024[Link]
NoteLLM-2: Multimodal Large Representation Models for RecommendationArxiv 2024[Link]
Multimodality Invariant Learning for Multimedia-Based New Item RecommendationArxiv 2024[Link]
SLMRec: Empowering Small Language Models for Sequential RecommendationArxiv 2024[Link]
Keyword-driven Retrieval-Augmented Large Language Models for Cold-start User RecommendationsArxiv 2024[Link]
Generating Query Recommendations via LLMsArxiv 2024[Link]
Large Language Models Enhanced Sequential Recommendation for Long-tail User and ItemArxiv 2024[Link]
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for RecommendationKDD 2024[Link]
LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based RankingArxiv 2024[Link]
A Practice-Friendly Two-Stage LLM-Enhanced Paradigm in Sequential RecommendationArxiv 2024[Link]
Large Language Models as Recommender Systems: A Study of Popularity BiasGen-IR@SIGIR24[Link]
Privacy in LLM-based Recommendation: Recent Advances and Future DirectionsArxiv 2024[Link]
An LLM-based Recommender System EnvironmentArxiv 2024[Link]
Robust Interaction-based Relevance Modeling for Online E-Commerce and LLM-based RetrievalECML-PKDD 2024[Link]
Large Language Models Make Sample-Efficient Recommender SystemsFCS[Link]
XRec: Large Language Models for Explainable RecommendationArxiv 2024[Link]
Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential RecommendationArxiv 2024[Link]
Large Language Models as Evaluators for Recommendation ExplanationsArxiv 2024[Link]
Text-like Encoding of Collaborative Information in Large Language Models for RecommendationACL 2024[Link]
Item-Language Model for Conversational RecommendationArxiv 2024[Link]
Improving LLMs for Recommendation with Out-Of-Vocabulary TokensArxiv 2024[Link]
On Softmax Direct Preference Optimization for RecommendationArxiv 2024[Link]
TokenRec: Learning to Tokenize ID for LLM-based Generative RecommendationArxiv 2024[Link]
DELRec: Distilling Sequential Pattern to Enhance LLM-based RecommendationArxiv 2024[Link]
TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired StrategyArxiv 2024[Link]
Multi-Layer Ranking with Large Language Models for News Source RecommendationSIGIR 2024[Link]
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information RetrievalArxiv 2024[Link]
LLM-enhanced Reranking in Recommender SystemsArxiv 2024[Link]
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario RecommendationArxiv 2024[Link]
Taxonomy-Guided Zero-Shot Recommendations with LLMsArxiv 2024[Link]
EAGER: Two-Stream Generative Recommender with Behavior-Semantic CollaborationKDD 2024[Link]
An Investigation of Prompt Variations for Zero-shot LLM-based RankersArxiv 2024[Link]
Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement LearningKDD 2024[Link]
Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware LearningArxiv 2024[Link]
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based RecommendationArxiv 2024[Link]
FIRST: Faster Improved Listwise Reranking with Single Token DecodingArxiv 2024[Link]
LLM-Powered Explanations: Unraveling Recommendations Through Subgraph ReasoningArxiv 2024[Link]
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking TaskArxiv 2024[Link]
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for RecommendationArxiv 2024[Link]
Generative Explore-Exploit: Training-free Optimization of Generative Recommender Systems using LLM OptimizersACL 2024[Link]
ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification QuestionsArxiv 2024[Link]
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language ModelsArxiv 2024[Link]
Preference Distillation for Personalized Generative RecommendationArxiv 2024[Link]
Towards Bridging the Cross-modal Semantic Gap for Multi-modal RecommendationArxiv 2024[Link]
Language Models Encode Collaborative Signals in RecommendationArxiv 2024[Link]
A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language ModelArxiv 2024[Link]
LLMGR: Large Language Model-based Generative Retrieval in Alipay SearchSIGIR 2024[Link]
Enhancing Sequential Recommenders with Augmented Knowledge from Aligned Large Language ModelsSIGIR 2024[Link]
Reinforced Prompt Personalization for Recommendation with Large Language ModelsArxiv 2024[Link]
Improving Retrieval in Sponsored Search by Leveraging Query Context SignalsArxiv 2024[Link]
Generative Retrieval with Preference Optimization for E-commerce SearchArxiv 2024[Link]
GenRec: Generative Personalized Sequential RecommendationArxiv 2024[Link]
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative RetrievalArxiv 2024[Link]
Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and InsightsCIKM 2024[Link]
Leveraging LLM Reasoning Enhances Personalized Recommender SystemsACL 2024[Link]
Multi-Aspect Reviewed-Item Retrieval via LLM Query Decomposition and Aspect FusionArxiv 2024[Link]
Lifelong Personalized Low-Rank Adaptation of Large Language Models for RecommendationArxiv 2024[Link]
Exploring Query Understanding for Amazon Product SearchArxiv 2024[Link]
A Decoding Acceleration Framework for Industrial Deployable LLM-based Recommender SystemsArxiv 2024[Link]
Prompt Tuning as User Inherent Profile Inference MachineArxiv 2024[Link]
Beyond Inter-Item Relations: Dynamic Adaptive Mixture-of-Experts for LLM-Based Sequential RecommendationArxiv 2024[Link]
Review-driven Personalized Preference Reasoning with Large Language Models for RecommendationArxiv 2024[Link]
DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender SystemArxiv 2024[Link]
LLM4DSR: Leveraing Large Language Model for Denoising Sequential RecommendationArxiv 2024[Link]
EasyRec: Simple yet Effective Language Models for RecommendationArxiv 2024[Link]
Collaborative Cross-modal Fusion with Large Language Model for RecommendationCIKM 2024[Link]
Customizing Language Models with Instance-wise LoRA for Sequential RecommendationArxiv 2024[Link]
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language ModelsArxiv 2024[Link]
CoRA: Collaborative Information Perception by Large Language Model's Weights for RecommendationArxiv 2024[Link]
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity PromptsArxiv 2024[Link]
Harnessing Multimodal Large Language Models for Multimodal Sequential RecommendationArxiv 2024[Link]
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender SystemsArxiv[Link]
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic UnderstandingRecSys 2024[Link]
SC-Rec: Enhancing Generative Retrieval with Self-Consistent Reranking for Sequential RecommendationArxiv 2024[Link]
Are LLM-based Recommenders Already the Best? Simple Scaled Cross-entropy Unleashes the Potential of Traditional Sequential RecommendersArxiv 2024[Link]
HRGraph: Leveraging LLMs for HR Data Knowledge Graphs with Information Propagation-based Job RecommendationKaLLM 2024[Link]
An Extremely Data-efficient and Generative LLM-based Reinforcement Learning Agent for RecommendersArxiv 2024[Link]
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM AgentKDD 2024[Link]
Laser: Parameter-Efficient LLM Bi-Tuning for Sequential Recommendation with Collaborative InformationArxiv 2024[Link]
MARS: Matching Attribute-aware Representations for Text-based Sequential RecommendationCIKM 2024[Link]
End-to-End Learnable Item Tokenization for Generative RecommendationArxiv 2024[Link]
Incorporate LLMs with Influential Recommender SystemArxiv 2024[Link]
Enhancing Sequential Recommendations through Multi-Perspective Reflections and IterationArxiv 2024[Link]
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLMArxiv 2024[Link]
Multilingual Prompts in LLM-Based Recommenders: Performance Across LanguagesArxiv 2024[Link]
Unleash LLMs Potential for Recommendation by Coordinating Twin-Tower Dynamic Semantic Token GeneratorArxiv 2024[Link]
Large Language Model Enhanced Hard Sample Identification for Denoising RecommendationArxiv 2024[Link]
Chain-of-thought prompting empowered generative user modeling for personalized recommendationNeural Computing and Applications[Link]
Challenging Fairness: A Comprehensive Exploration of Bias in LLM-Based RecommendationsArxiv 2024[Link]
Decoding Style: Efficient Fine-Tuning of LLMs for Image-Guided Outfit Recommendation with PreferenceCIKM 2024[Link]
LLM-Powered Text Simulation Attack Against ID-Free Recommender SystemsArxiv 2024[Link]
FLARE: Fusing Language Models and Collaborative Architectures for Recommender EnhancementArxiv 2024[Link]
Retrieve, Annotate, Evaluate, Repeat: Leveraging Multimodal LLMs for Large-Scale Product Retrieval EvaluationArxiv 2024[Link]
HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User ModelingArxiv 2024[Link]
Large Language Model Ranker with Graph Reasoning for Zero-Shot RecommendationICANN 2024[Link]
User Knowledge Prompt for Sequential RecommendationRecSys 2024[Link]
RLRF4Rec: Reinforcement Learning from Recsys Feedback for Enhanced Recommendation RerankingArxiv 2024[Link]
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External ServicesArxiv 2024[Link]
TLRec: A Transfer Learning Framework to Enhance Large Language Models for Sequential Recommendation TasksRecSys 2024[Link]
SeCor: Aligning Semantic and Collaborative Representations by Large Language Models for Next-Point-of-Interest RecommendationsRecSys 2024[Link]
Efficient Inference for Large Language Model-based Generative RecommendationArxiv 2024[Link]
Instructing and Prompting Large Language Models for Explainable Cross-domain RecommendationsRecSys 2024[Link]
ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning PoolRecSys 2024[Link]
Inductive Generative Recommendation via Retrieval-based SpeculationArxiv 2024[Link]
Constructing and Masking Preference Profile with LLMs for Filtering Discomforting RecommendationArxiv 2024[Link]
Towards Scalable Semantic Representation for RecommendationArxiv 2024[Link]
Large Language Models as Narrative-Driven RecommendersArxiv 2024[Link]
The Moral Case for Using Language Model Agents for RecommendationArxiv 2024[Link]
RosePO: Aligning LLM-based Recommenders with Human ValuesArxiv 2024[Link]
Comprehending Knowledge Graphs with Large Language Models for Recommender SystemsArxiv 2024[Link]
Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior RecommendationsArxiv 2024[Link]
Improving Pinterest Search Relevance Using Large Language ModelsCIKM 2024 Workshop[Link]
STAR: A Simple Training-free Approach for Recommendations using Large Language ModelsArxiv 2024[Link]
End-to-end Training for Recommendation with Language-based User ProfilesArxiv 2024[Link]
Knowledge Graph Enhanced Language Agents for RecommendationArxiv 2024[Link]
Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMsArxiv 2024[Link]
Real-Time Personalization for LLM-based Recommendation with Customized In-Context LearningArxiv 2024[Link]
ReasoningRec: Bridging Personalized Recommendations and Human-Interpretable Explanations through LLM ReasoningArxiv 2024[Link]
Beyond Utility: Evaluating LLM as RecommenderArxiv 2024[Link]
Enhancing ID-based Recommendation with Large Language ModelsArxiv 2024[Link]
LLM4PR: Improving Post-Ranking in Search Engine with Large Language ModelsArxiv 2024[Link]
Proactive Detection and Calibration of Seasonal Advertisements with Multimodal Large Language ModelsArxiv 2024[Link]
Enhancing ID-based Recommendation with Large Language ModelsArxiv 2024[Link]
Transferable Sequential Recommendation via Vector Quantized Meta LearningArxiv 2024[Link]
Self-Calibrated Listwise Reranking with Large Language ModelsArxiv 2024[Link]
Enhancing Large Language Model Based Sequential Recommender Systems with Pseudo Labels ReconstructionACL Findings 2024[Link]
Unleashing the Power of Large Language Models for Group POI RecommendationsAvrxi 2024[Link]
Scaling Laws for Online Advertisement RetrievalArxiv 2024[Link]
Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance LearningArxiv 2024[Link]
GOT4Rec: Graph of Thoughts for Sequential RecommendationArxiv 2024[Link]
HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender SystemsArxiv 2024[Link]
Cross-Domain Recommendation Meets Large Language ModelsArxiv 2024[Link]
Explainable CTR Prediction via LLM ReasoningWSDM 2025[Link]
Enabling Explainable Recommendation in E-commerce with LLM-powered Product Knowledge GraphIJCAI Workshop 2025[Link]
Break the ID-Language Barrier: An Adaption Framework for Sequential RecommendationArxiv 2024[Link]
LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender SystemArxiv 2024[Link]
Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language ModelsArxiv 2024[Link]
ULMRec: User-centric Large Language Model for Sequential RecommendationArxiv 2024[Link]
AltFS: Agency-light Feature Selection with Large Language Models in Deep Recommender SystemsArxiv 2024[Link]
MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI RecommendationArxiv 2024[Link]
MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced InterpretationArxiv 2024[Link]
SPRec: Leveraging Self-Play to Debias Preference Alignment for Large Language Model-based RecommendationsArxiv 2024[Link]
RecSys Arena: Pair-wise Recommender System Evaluation with Large Language ModelsArxiv 2024[Link]
CRS Arena: Crowdsourced Benchmarking of Conversational Recommender SystemsArxiv 2024[Link]
Boosting LLM-based Relevance Modeling with Distribution-Aware Robust LearningArxiv 2024[Link]
LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential RecommendationArxiv 2024[Link]
Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language ModelsArxiv 2024[Link]
Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language ModelsArxiv 2024[Link]
ChainRank-DPO: Chain Rank Direct Preference Optimization for LLM RankersArxiv 2024[Link]
Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation SystemsArxiv 2024[Link]
</p > </details>

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

DatasetRS ScenarioLink
AmazonQACQuery Autocomplete[Link]
NineRec9 Domains[Link]
MicroLensVideo Streaming[Link]
Amazon-Review 2023E-commerce[Link]
Reddit-MovieConversational & Movie[Link]
Amazon-M2E-commerce[Link]
MovieLensMovie[Link]
AmazonE-commerce[Link]
BookCrossingBook[Link]
GoodReadsBook[Link]
AnimeAnime[Link]
PixelRecShort Video[Link]
NetflixMovie[Link]

2.2 Benchmarks

BenchmarksWebcite LinkPaper
Shopping MMLU[Paper]
Amazon-M2 (KDD Cup 2023)[Link][Paper]
LLMRec[Link][Paper]
OpenP5[Link][Paper]
TABLET[Link][Paper]

3. Related Repositories

Repo NameMaintainer
rs-llm-paper-listwwliu555
awesome-recommend-system-pretraining-papersarchersama
LLM4RecWLiK
Awesome-LLM4RS-Papersnancheng58
LLM4IR-SurveyRUC-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}
}