This repository collects the latest research progress of Contrastive Learning (CL) and Data Augmentation (DA) in Recommender Systems. Comments and contributions are welcome.
CF = Collaborative Filtering, SSL = Self-Supervised Learning
- Survey/Tutorial/Framework Total Papers: 6
- Only Data Augmentation Total Papers: 39
- Graph Models with CL Total Papers: 108
- Sequential Models with CL Total Papers: 94
- Other Tasks with CL Total Papers: 104
-
Contrastive Self-supervised Learning in Recommender Systems: A Survey (Survey)
arXiv 2023, [PDF]
-
Self-Supervised Learning for Recommender Systems A Survey (Survey + Framework)
-
Self-Supervised Learning in Recommendation: Fundamentals and Advances (Tutorial)
WWW 2022, [Web]
-
Tutorial: Self-Supervised Learning for Recommendation: Foundations, Methods and Prospects (Tutorial)
DASFAA 2023, [Web]
-
SSLRec: A Self-Supervised Learning Framework for Recommendation (Framework)
-
A Comprehensive Survey on Self-Supervised Learning for Recommendation (Survey)
-
Enhancing Collaborative Filtering with Generative Augmentation (CF + GAN + DA)
KDD 2019, [PDF]
-
Future Data Helps Training Modeling Future Contexts for Session-based Recommendation (Session + DA)
-
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer (Sequential + DA)
-
Self-Knowledge Distillation with Bidirectional Chronological Augmentation of Transformer for Sequential Recommendation (Sequential + DA)
-
Counterfactual Data-Augmented Sequential Recommendation (Sequential + Counterfactual + DA)
SIGIR 2021, [PDF]
-
CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation (Sequential + Counterfactual + DA)
SIGIR 2021, [PDF]
-
Effective and Efficient Training for Sequential Recommendation using Recency Sampling (Sequential + DA)
RecSys 2022, [PDF]
-
Data Augmentation Strategies for Improving Sequential Recommender Systems (Sequential + DA)
-
Learning to Augment for Casual User Recommendation (Sequential + DA)
WWW 2022, [PDF]
-
Recency Dropout for Recurrent Recommender Systems (RNN + DA)
arXiv 2022, [PDF]
-
Improved Recurrent Neural Networks for Session-based Recommendations (RNN + DA)
DLRS 2016, [PDF]
-
Bootstrapping User and Item Representations for One-Class Collaborative Filtering (CF + Graph + DA)
-
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems (Graph + DA)
-
Improving Recommendation Fairness via Data Augmentation (Fairness + DA)
-
Fairly Adaptive Negative Sampling for Recommendations (Fairness + DA)
WWW 2023, [PDF]
-
Creating Synthetic Datasets for Collaborative Filtering Recommender Systems using Generative Adversarial Networks (CF + DA)
arXiv 2023, [PDF]
-
Graph Collaborative Signals Denoising and Augmentation for Recommendation (CF + DA)
-
Data Augmented Sequential Recommendation based on Counterfactual Thinking (Sequential + DA)
TKDE 2022, [PDF]
-
Multi-Epoch Learning for Deep Click-Through Rate Prediction Models (CRT + DA)
arXiv 2023, [PDF]
-
Improving Conversational Recommendation Systems via Counterfactual Data Simulation (Conversational Rec + DA)
-
Disentangled Variational Auto-encoder Enhanced by Counterfactual Data for Debiasing Recommendation (Debias Rec + DA)
arXiv 2023, [PDF]
-
Domain Disentanglement with Interpolative Data Augmentation for Dual-Target Cross-Domain Recommendation (Cross-Domain + DA)
RecSys 2023, [PDF]
-
Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions (Session + DA)
RecSys 2023, [PDF]
-
Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation (RL Rec + DA)
arXiv 2022, [PDF]
-
Augmented Negative Sampling for Collaborative Filtering (CF + DA)
-
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Sequential + DA)
RecSys 2023, [PDF]
-
Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation (DA)
arXiv 2023, [PDF]
-
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems (Graph + DA)
-
Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation (Graph + DA)
arXiv 2023, [PDF]
-
Diffusion Augmentation for Sequential Recommendation (Sequential + DA)
-
Large Language Models as Data Augmenters for Cold-Start Item Recommendation (DA)
arXiv 2024, [PDF]
-
SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation (Sequential + DA)
-
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation (DA)
arXiv 2024, [PDF]
-
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation (DA)
-
Repeated Padding as Data Augmentation for Sequential Recommendation (Sequential + DA)
arXiv 2024, [PDF]
-
Rethinking sequential relationships: Improving sequential recommenders with inter-sequence data augmentation (Sequential + DA)
amazon.science 2024, [PDF]
-
Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation (POI Rec + DA)
TOIS 2024, [PDF]
-
TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation (POI Rec + DA)
AAAI 2024, [PDF]
-
Improving Long-Tail Item Recommendation with Graph Augmentation (Graph + DA)
CIKM 2023, [PDF]
-
Self-supervised Graph Learning for Recommendation (Graph + CL + DA)
-
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation (Graph + CL)
-
Are graph augmentations necessary? simple graph contrastive learning for recommendation (Graph + CL)
-
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation (Graph + CL)
-
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation (Graph + CL + DA)
arXiv 2022, [PDF]
-
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation (POI Rec, Graph + CL + DA)
-
An MLP-based Algorithm for Efficient Contrastive Graph Recommendations (Graph + CL + DA)
SIGIR 2022, [PDF]
-
A Review-aware Graph Contrastive Learning Framework for Recommendation (Graph + CL + DA)
-
Simple Yet Effective Graph Contrastive Learning for Recommendation (Graph + CL + DA)
-
Contrastive Meta Learning with Behavior Multiplicity for Recommendation (Graph + CL + DA)
-
Disentangled Contrastive Learning for Social Recommendation (Graph + CL + DA)
CIKM 2022, [PDF]
-
Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning (Graph + CL)
-
Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System (Graph + CL)
-
Knowledge Graph Contrastive Learning for Recommendation (Graph + DA + CL)
-
Temporal Knowledge Graph Reasoning with Historical Contrastive Learning (Graph + CL)
-
Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation (Graph + SSL)
-
SAIL: Self-Augmented Graph Contrastive Learning (Graph + CL)
AAAI 2022, [PDF]
-
Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
-
Socially-Aware Self-Supervised Tri-Training for Recommendation (Graph + CL)
-
Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
-
Multi-Behavior Dynamic Contrastive Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
-
Self-Augmented Recommendation with Hypergraph Contrastive Collaborative Filtering (Graph + CL)
-
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning (Graph + CF + CL)
-
Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation (Graph + CL)
-
Hypergraph Contrastive Collaborative Filtering (Graph + CF + CL + DA)
-
Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems (Graph + CL)
-
Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation (Group Rec, Graph + CL + DA)
-
Self-Supervised Hypergraph Transformer for Recommender Systems (Graph + SSL)
-
Episodes Discovery Recommendation with Multi-Source Augmentations (Graph + DA + CL)
arXiv 2023, [PDF]
-
Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation (Graph + Sequential + CL)
TOIS 2023, [PDF]
-
Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation (Graph + DA + CL)
DASFAA 2023, [PDF]
-
SimCGNN: Simple Contrastive Graph Neural Network for Session-based Recommendation (Graph + CL)
arXiv 2023, [PDF]
-
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning (Graph + DA + CL)
-
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation (Graph + Session + CL)
-
Self-Supervised Graph Co-Training for Session-based Recommendation (Graph + Session + CL)
-
Heterogeneous Graph Contrastive Learning for Recommendation (Graph + CL)
-
Automated Self-Supervised Learning for Recommendation (Graph + DA + CL)
-
Graph-less Collaborative Filtering (Graph + CL)
-
Disentangled Contrastive Collaborative Filtering (Graph + CL)
-
Knowledge-refined Denoising Network for Robust Recommendation (Graph + CL)
-
Disentangled Graph Contrastive Learning for Review-based Recommendation (Graph + CL)
IJCAI 2023, [PDF]
-
Adaptive Graph Contrastive Learning for Recommendation (Graph + CL)
-
Knowledge Enhancement for Contrastive Multi-Behavior Recommendation (Graph + CL)
-
Contrastive Meta Learning with Behavior Multiplicity for Recommendation (Graph + CL)
-
Graph Transformer for Recommendation (Graph + CL)
-
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation (Graph + CL)
CIKM 2023, [PDF]
-
Knowledge Graph Self-Supervised Rationalization for Recommendation (Graph + CL)
-
Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization (Graph + CL)
SIGIR 2021, [PDF]
-
Generative-Contrastive Graph Learning for Recommendation (Graph + CL)
SIGIR 2023, [PDF]
-
AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering (Graph + CL)
-
Candidate–aware Graph Contrastive Learning for Recommendation (Graph + CL)
-
Multi-View Graph Convolutional Network for Multimedia Recommendation (Graph + CL)
-
Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation (Graph + CL)
SIGIR 2023, [PDF]
-
uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering (Graph + CL)
-
Contrastive Box Embedding for Collaborative Reasoning (Graph + CL)
SIGIR 2023, [PDF]
-
Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph (Graph + CL)
CIKM 2023, [PDF]
-
Contrastive Graph Prompt-tuning for Cross-domain Recommendation (Graph + CL)
arXiv 2023, [PDF]
-
Dual Intents Graph Modeling for User-centric Group Discovery (Graph + CL)
-
Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning (Graph + CL)
-
Multi-Relational Contrastive Learning for Recommendation (Graph + CL)
-
Multi-behavior Recommendation with SVD Graph Neural Networks (Graph + CL)
arXiv 2023, [PDF]
-
E-commerce Search via Content Collaborative Graph Neural Network (Graph + DA + CL)
-
Long-tail Augmented Graph Contrastive Learning for Recommendation (Graph + DA + CL)
-
LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning (Graph + CL)
-
On the Sweet Spot of Contrastive Views for Knowledge-enhanced Recommendation (Graph + CL)
-
Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering (Graph + CL)
-
Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering (Graph + CL)
TOIS 2023, [PDF]
-
TDCGL: Two-Level Debiased Contrastive Graph Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
-
Topology-aware Debiased Self-supervised Graph Learning for Recommendation (Graph + CL)
-
Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering (Graph + DA + CL)
-
Contrastive Multi-Level Graph Neural Networks for Session-based Recommendation (Graph + CL)
TMM 2023, [PDF]
-
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations (Graph + CL)
-
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations (Graph + CL)
-
Denoised Self-Augmented Learning for Social Recommendation (Graph + CL)
-
Intent-aware Recommendation via Disentangled Graph Contrastive Learning (Graph + CL)
IJCAI 2023, [PDF]
-
GENET: Unleashing the Power of Side Information for Recommendation via Hypergraph Pre-training (Graph + CL)
arXiv 2023, [PDF]
-
Graph Pre-training and Prompt Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
-
Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning (Graph + CL)
-
ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation (Graph + Multi-Modal + CL)
arXiv 2023, [PDF]
-
Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems (Graph + LLM + CL)
arXiv 2023, [PDF]
-
LGMRec: Local and Global Graph Learning for Multimodal Recommendation (Graph + Multi-Modal + CL)
-
RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
-
DiffKG: Knowledge Graph Diffusion Model for Recommendation (Graph + CL)
-
QoS-Aware Graph Contrastive Learning for Web Service Recommendation (Graph + CL)
arXiv 2024, [PDF]
-
Challenging Low Homophily in Social Recommendation (Graph + CL)
WWW 2024, [PDF]
-
RecDCL: Dual Contrastive Learning for Recommendation (Graph + CL)
-
Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course Recommendation (Graph + CL)
TKDD 2024, [PDF]
-
Graph Contrastive Learning With Negative Propagation for Recommendation (Graph + CL)
TCSS 2024, [PDF]
-
General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout (Graph + CL)
-
Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph (Graph + CL)
arXiv 2024, [PDF]
-
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling (Graph + CL)
-
Self-supervised Contrastive Learning for Implicit Collaborative Filtering (Graph + DA + CL)
arXiv 2024, [PDF]
-
Dual-Channel Multiplex Graph Neural Networks for Recommendation (Graph + CL)
arXiv 2024, [PDF]
-
Bilateral Unsymmetrical Graph Contrastive Learning for Recommendation (Graph + CL)
arXiv 2024, [PDF]
-
Knowledge-aware Dual-side Attribute-enhanced Recommendation (Graph + CL)
-
A Progressively-Passing-then-Disentangling Approach to Recipe Recommendation (Graph + CL)
TMM 2024, [PDF]
-
Graph Augmentation for Recommendation (Graph + DA + CL)
-
One Backpropagation in Two Tower Recommendation Models (Graph + CL)
arXiv 2024, [PDF]
-
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users (Graph + CL)
COLING 2024, [PDF]
-
Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations (Graph + Social Rec + CL)
-
Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation (Graph + CL)
AAAI 2024, [PDF]
-
A Directional Diffusion Graph Transformer for Recommendation (Graph + CL)
SIGIR 2024, [PDF]
-
Heterogeneous Adaptive Preference Learning for Recommendation (Graph + CL)
-
Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Diversification-Enhancing Contrastive Learning (Graph + CL)
-
Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation (Graph + CL)
-
Enhanced Hierarchical Contrastive Learning for Recommendation (Graph + CL)
AAAI 2024, [PDF]
-
How to Improve Representation Alignment and Uniformity in Graph-based Collaborative Filtering? (Graph + CL)
-
PopDCL: Popularity-aware Debiased Contrastive Loss for Collaborative Filtering (Graph + CL)
CIKM 2023, [PDF]
-
Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation (Sequential + CL + DA)
-
Contrastive Learning for Sequential Recommendation (Sequential + CL + DA)
-
Contrastive Self-supervised Sequential Recommendation with Robust Augmentation (Sequential + CL + DA)
-
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation (Sequential + CL + DA)
arXiv 2022, [PDF]
-
S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization (Sequential + CL + DA)
-
Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation (Sequential + CL + DA)
-
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation (Sequential + CL + DA)
-
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation (Sequential + CL + DA)
ICDM 2021, [PDF]
-
Contrastive Learning with Bidirectional Transformers for Sequential Recommendation (Sequential + CL + DA)
-
ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation (Sequential + CL + DA)
-
Temporal Contrastive Pre-Training for Sequential Recommendation (Sequential + CL + DA)
-
Multi-level Contrastive Learning Framework for Sequential Recommendation (Graph + Sequential + CL)
CIKM 2022, [PDF]
-
Equivariant Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Explanation Guided Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Intent Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Dual Contrastive Network for Sequential Recommendation (Sequential + CL)
SIGIR 2022, [PDF]
-
Dual Contrastive Network for Sequential Recommendation with User and Item-Centric Perspectives (Sequential + CL)
arXiv 2022, [PDF]
-
Enhancing Sequential Recommendation with Graph Contrastive Learning (Sequential + Graph + CL + DA)
-
Disentangling Long and Short-Term Interests for Recommendation (Sequential + Graph + CL)
-
Hyperbolic Hypergraphs for Sequential Recommendation (Sequential + Graph + CL + DA)
-
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation (Sequential + CL)
-
Dual-interest Factorization-heads Attention for Sequential Recommendation (Sequential + CL)
-
GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation (Sequential + DA + CL)
arXiv 2023, [PDF]
-
Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation (Sequential + CL)
-
A Self-Correcting Sequential Recommender (Sequential + DA + SSL)
-
User Retention-oriented Recommendation with Decision Transformer (Sequential + CL)
-
Debiased Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders (Sequential + CL)
-
Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning (Multi-Modal + Sequential + CL)
arXiv 2023, [PDF]
-
Sequential Recommendation with Diffusion Models (Diffsion + Sequential + CL)
arXiv 2023, [PDF]
-
Triple Sequence Learning for Cross-domain Recommendation (Sequential + CL)
arXiv 2023, [PDF]
-
Contrastive Cross-Domain Sequential Recommendation (Cross-Domain + Sequential + CL)
-
Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation (VAE + Sequential + CL)
-
Meta-optimized Contrastive Learning for Sequential Recommendation (Meta + Sequential + CL)
-
Frequency Enhanced Hybrid Attention Network for Sequential Recommendation (Sequential + CL)
-
Self-Supervised Multi-Modal Sequential Recommendation (Multi-Moda + Sequential + CL)
-
Conditional Denoising Diffusion for Sequential Recommendation (Diffusion + Sequential + CL)
arXiv 2023, [PDF]
-
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation (Diffusion + Sequential + CL)
-
Multi-view Multi-behavior Contrastive Learning in Recommendation (Sequential + Graph + CL)
-
Denoising Multi-modal Sequential Recommenders with Contrastive Learning (Sequential + CL)
arXiv 2023, [PDF]
-
Multi-view Multi-behavior Contrastive Learning in Recommendation (Sequential + Graph + CL)
-
Contrastive Enhanced Slide Filter Mixer for Sequential Recommendation (Sequential + CL)
-
Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems (Sequential + DA + CL)
-
When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation (Sequential + CL)
-
Text Is All You Need: Learning Language Representations for Sequential Recommendation (Sequential + CL)
KDD 2023, [PDF]
-
Sequential Recommendation with Multiple Contrast Signals (Sequential + CL)
-
Robust Reinforcement Learning Objectives for Sequential Recommender Systems (Sequential + CL)
-
AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation (Sequential + CL)
PMLR 2023, [PDF]
-
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation (Sequential + CL)
PMLR 2023, [PDF]
-
Hierarchical Contrastive Learning with Multiple Augmentation for Sequential Recommendation (Sequential + DA + CL)
arXiv 2023, [PDF]
-
Poisoning Self-supervised Learning Based Sequential Recommendations (Sequential + Attack + DA + CL)
-
Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation (Sequential + CL)
SIGIR 2023, [PDF]
-
Leveraging Negative Signals with Self-Attention for Sequential Music Recommendation (Sequential + CL)
RecSys 2023, [PDF]
-
RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendationn (Sequential + DA + CL)
CIKM 2023, [PDF]
-
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning (Sequential + DA + CL)
-
Unbiased and Robust: External Attention-enhanced Graph Contrastive Learning for Cross-domain Sequential Recommendation (Sequential + Graph + DA + CL)
-
Dual-Scale Interest Extraction Framework with Self-Supervision for Sequential Recommendation (Sequential + CL)
arXiv 2023, [PDF]
-
Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation (Sequential + DA + CL)
-
Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation (Sequential + CL)
arXiv 2023, [PDF]
-
Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation (Sequential + Graph + CL)
-
Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach (Sequential + CL)
arXiv 2023, [PDF]
-
Feature-Level Deeper Self-Attention Network With Contrastive Learning for Sequential Recommendation (Sequential + CL)
TKDE 2023, [PDF]
-
Learnable Model Augmentation Contrastive Learning for Sequential Recommendation (Sequential + CL)
TKDE 2023, [PDF]
-
Learnable Model Augmentation Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
-
Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation (Sequential + CL)
-
Cracking the Code of Negative Transfer:A Cooperative Game Theoretic Approach for Cross-Domain Sequential Recommendation (Sequential + Cross-Domain + CL)
CIKM 2023, [PDF]
-
Contrastive Multi-View Interest Learning for Cross-Domain Sequential Recommendation (Sequential + Cross-Domain + CL)
-
E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation (Sequential + LLM + CL)
-
TFCSRec: Time-Frequency Consistency Based Contrastive Learning for Sequential Recommendation (Sequential + CL)
Expert Systems with Applications 2024, [PDF]
-
A Relevant and Diverse Retrieval-enhanced Data Augmentation Framework for Sequential Recommendation (Sequential + DA + CL)
-
high-level preferences as positive examples in contrastive learning for multi-interest sequential recommendation (Sequential + CL)
Arxiv 2023, [PDF]
-
Feature-Aware Contrastive Learning with Bidirectional Transformers for Sequential Recommendation (Sequential + CL)
TKDE 2023, [PDF]
-
LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks with Graph Contrastive Learning (Sequential + Graph + CL)
Access 2023, [PDF]
-
End-to-end Learnable Clustering for Intent Learning in Recommendation (Sequential + CL)
arXiv 2024, [PDF]
-
Contrastive Learning with Frequency-Domain Interest Trends for Sequential Recommendation (Sequential + DA + CL)
-
Sequential Recommendation on Temporal Proximities with Contrastive Learning and Self-Attention (Sequential + CL)
-
End-to-end Graph-Sequential Representation Learning for Accurate Recommendations (Sequential + Graph + CL)
-
Multi-Sequence Attentive User Representation Learning for Side-information Integrated Sequential Recommendation (Sequential + CL)
-
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness (Sequential + CL)
arxiv 2024, [PDF]
-
Collaborative Sequential Recommendations via Multi-View GNN-Transformers (Sequential + Graph + CL)
TOIS 2024, [PDF]
-
Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation (Sequential + DA + CL)
-
Diversifying Sequential Recommendation with Retrospective and Prospective Transformers (Sequential + CL)
-
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment Recommendation (Sequential + CL)
-
Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation (Sequential + CL)
WWW 2024, [PDF]
-
Temporal Graph Contrastive Learning for Sequential Recommendation (Sequential + Graph + CL)
AAAI 2024, [PDF]
-
Sparse Enhanced Network: An Adversarial Generation Method for Robust Augmentation in Sequential Recommendation (Sequential + DA + CL)
-
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention (Sequential + CL)
-
Beyond the Sequence: Statistics-Driven Pre-training for Stabilizing Sequential Recommendation Model (Sequential + DA + CL)
RecSys 2023, [PDF]
-
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation (Sequential + DA + CL)
-
UniSAR: Modeling User Transition Behaviors between Search and Recommendation (Sequential + CL)
-
Multi-Level Sequence Denoising with Cross-Signal Contrastive Learning for Sequential Recommendation (Sequential + CL)
-
Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement (Sequential + CL)
arXiv 2024, [PDF]
-
CL4CTR: A Contrastive Learning Framework for CTR Prediction (CTR + CL)
-
CCL4Rec: Contrast over Contrastive Learning for Micro-video Recommendation (Micro Video + CL)
arXiv 2022, [PDF]
-
Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation (Multi Interest + CL)
-
Interventional Recommendation with Contrastive Counterfactual Learning for Better Understanding User Preferences (Counterfactual + DA + CL)
arXiv 2022, [PDF]
-
Multi-granularity Item-based Contrastive Recommendation (Industry + CL)
arXiv 2022, [PDF]
-
Improving Micro-video Recommendation via Contrastive Multiple Interests (Micro Video + CL)
SIGIR 2022, [PDF]
-
Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning (Music Rec + CL)
-
Self-supervised Learning for Large-scale Item Recommendations (Industry + CL + DA)
CIKM 2021, [PDF]
-
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation (Bundle Rec + CL)
-
Contrastive Learning for Cold-start Recommendation (Cold Start + CL)
ACM MM (ACM International Conference on Multimedia) 2021, [PDF], [Code]
-
Socially-aware Dual Contrastive Learning for Cold-Start Recommendation (Cold Start + CL)
SIGIR 2022, [PDF]
-
Multi-modal Graph Contrastive Learning for Micro-video Recommendation (Cold Start + Graph + CL)
SIGIR 2022, [PDF]
-
Self-supervised Learning for Multimedia Recommendation (Multi Media + Graph + DA + CL)
-
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering (CF + Graph + DA + CL)
ACM MM (ACM International Conference on Multimedia) 2021, [PDF], [Code]
-
Trading Hard Negatives and True Negatives:A Debiased Contrastive Collaborative Filtering Approach (CF + CL)
IJCAI 2022, [PDF]
-
The World is Binary: Contrastive Learning for Denoising Next Basket Recommendation (Next Basket + CL)
SIGIR 2021, [PDF]
-
MIC: Model-agnostic Integrated Cross-channel Recommender (Industry + CL + DA)
CIKM 2022, [PDF]
-
A Contrastive Sharing Model for Multi-Task Recommendation (Multi Task + CL)
WWW 2022, [PDF]
-
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System (Conversational Rec + CL)
-
Contrastive Cross-domain Recommendation in Matching (Cross-domain Rec + DA + CL)
-
Contrastive Cross-Domain Sequential Recommendation (Cross-Domain + Sequential + CL)
-
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations (Industry + CL + DA)
-
Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation (GNN + CL)
TOIS 2022, under review, [PDF]
-
Disentangled Causal Embedding With Contrastive Learning For Recommender System (Causal + CL)
-
Contrastive Collaborative Filtering for Cold-Start Item Recommendation (CF + Cold Start + CL)
-
Cross-domain recommendation via user interest alignment (Cross-Domain Rec + CL)
-
Multi-Modal Self-Supervised Learning for Recommendation (Multi Modal Rec + CL)
-
Efficient On-Device Session-Based Recommendation (Session + DA + CL)
-
On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation (Session + DA + CL)
-
Modality Matches Modality: Pretraining Modality-Disentangled Item Representations for Recommendation (Multi Modal Rec + CL)
-
End-to-End Personalized Next Location Recommendation via Contrastive User Preference Modeling (POI Rec + CL)
arXiv 2023, [PDF]
-
Bootstrap Latent Representations for Multi-modal Recommendation (Multi Modal Rec + CL)
-
Simplifying Content-Based Neural News Recommendation: On User Modeling and Training Objectives (News Rec + CL)
-
Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search (CTR + CL)
CIKM 2022, [PDF]
-
Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck (Cross-Domain + CL)
-
DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation (Cross-Domain + CL)
-
Towards Universal Cross-Domain Recommendation (Cross-domain + CL)
-
Dual-Ganularity Contrastive Learning for Session-based Recommendation (Session + CL)
arXiv 2023, [PDF]
-
Discreetly Exploiting Inter-session Information for Session-based Recommendation (Session Rec + CL)
arXiv 2023, [PDF]
-
PerCoNet: News Recommendation with Explicit Persona and Contrastive Learning (News Rec + CL)
arXiv 2023, [PDF]
-
Hierarchical and Contrastive Representation Learning for Knowledge-aware Recommendation (Knowledge Aware + CL)
ICME 2023, [PDF]
-
Attention-guided Multi-step Fusion: A Hierarchical Fusion Network for Multimodal Recommendation (Multi Modal + CL)
SIGIR 2023, [PDF]
-
PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training (Fed Rec + CL)
arXiv 2023, [PDF]
-
UniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based Recommendation (Text Based Rec + CL)
-
Attention-guided Multi-step Fusion: A Hierarchical Fusion Network for Multimodal Recommendation (Multi Behavior + CL)
-
Learning Similarity among Users for Personalized Session-Based Recommendation from hierarchical structure of User-Session-Item (Session Rec + CL)
arXiv 2023, [PDF]
-
Securing Visually-Aware Recommender Systems: An Adversarial Image Reconstruction and Detection Framework (Visually Rec + CL)
arXiv 2023, [PDF]
-
Disentangled Contrastive Learning for Cross-Domain Recommendation (Cross-Domain + CL)
DASFAA 2023, [PDF]
-
ContentCTR: Frame-level Live Streaming Click-Through Rate Prediction with Multimodal Transformer (CTR + CL)
arXiv 2023, [PDF]
-
ContentCTR: Frame-level Live Streaming Click-Through Rate Prediction with Multimodal Transformer (CVR + CL)
-
Language-Enhanced Session-Based Recommendation with Decoupled Contrastive Learning (Session Rec + CL)
-
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation (Conversational Rec + CL)
-
Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation (Bundle Rec + CL)
-
Contrastive Learning for Conversion Rate Prediction (CVR + CL)
-
Review-based Multi-intention Contrastive Learning for Recommendation (Review + CL)
SIGIR 2023, [PDF]
-
CSPM: A Contrastive Spatiotemporal Preference Model for CTR Prediction in On-Demand Food Delivery Services (CTR + CL)
CIKM 2023, [PDF]
-
MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation (Multi Modal + CL)
-
MUSE: Music Recommender System with Shuffle Play Recommendation Enhancement (Music Rec + DA + CL)
-
Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation (Review + CL)
TOIS 2023, [PDF]
-
Interpretable User Retention Modeling in Recommendation (User Modelling + CL)
-
Beyond Co-occurrence: Multi-modal Session-based Recommendation (Session Rec + CL)
-
Representation Learning with Large Language Models for Recommendation (LLM + CL)
-
Universal Multi-modal Multi-domain Pre-trained Recommendation (Pre-trained + CL)
arXiv 2023, [PDF]
-
Towards Hierarchical Intent Disentanglement for Bundle Recommendation (Bundle Rec + CL)
TKDE 2023, [PDF]
-
ControlRec: Bridging the Semantic Gap between Language Model and Personalized Recommendation (LLM + CL)
arXiv 2023, [PDF]
-
Enhancing Item-level Bundle Representation for Bundle Recommendation (Bundle Rec + CL)
-
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation (Bundle Rec + CL)
-
Poisoning Attacks Against Contrastive Recommender Systems (Attack Rec + CL)
arXiv 2023, [PDF]
-
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation (Cross-domain + CL)
WSDM 2024, [PDF]
-
(Debiased) Contrastive Learning Loss for Recommendation (Technical Report) (Analysis + CL)
arXiv 2023, [PDF]
-
Revisiting Recommendation Loss Functions through Contrastive Learning (Technical Report) (Analysis + CL)
arXiv 2023, [PDF]
-
Hierarchical Alignment With Polar Contrastive Learning for Next-Basket Recommendation (Next Basket + CL)
TKDE 2023, [PDF]
-
CETN: Contrast-enhanced Through Network for CTR Prediction (CTR + CL)
arXiv 2023, [PDF]
-
Multi-Modality is All You Need for Transferable Recommender Systems (Transferable Rec + CL)
-
RIGHT: Retrieval-augmented Generation for Mainstream Hashtag Recommendation (Hashtag Rec + CL)
-
AT4CTR: Auxiliary Match Tasks for Enhancing Click-Through Rate Prediction (CTR + CL)
AAAI 2024, [PDF]
-
Attribute-driven Disentangled Representation Learning for Multimodal Recommendation (Multi Modal + CL)
arXiv 2023, [PDF]
-
TopicVAE: Topic-aware Disentanglement Representation Learning for Enhanced Recommendation (Multi Modal + CL)
-
Disentangled CVAEs with Contrastive Learning for Explainable Recommendation (Explainable + CL)
AAAI 2023, [PDF]
-
DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation (Rec + CL)
-
Self-Supervised Learning for User Sequence Modeling (Rec + CL)
arXiv 2023, [PDF]
-
RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation (LLM + CL)
arXiv 2024, [PDF]
-
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation (Counterfactual + CL)
arXiv 2024, [PDF]
-
Non-autoregressive Generative Models for Reranking Recommendation (Reranking + CL)
arXiv 2024, [PDF]
-
Modeling Balanced Explicit and Implicit Relations with Contrastive Learning for Knowledge Concept Recommendation in MOOCs (MOOC Rec + CL)
arXiv 2024, [PDF]
-
MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation (Multi Modal + CL)
-
NoteLLM: A Retrievable Large Language Model for Note Recommendation (Note Rec + CL)
WWW 2024, [PDF]
-
A Privacy-Preserving Framework with Multi-Modal Data for Cross-Domain Recommendation (Cross-Domain + CL)
arXiv 2024, [PDF]
-
PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction (CTR + CL)
WWW 2024, [PDF]
-
An Aligning and Training Framework for Multimodal Recommendations (Multi Modal + CL)
arXiv 2024, [PDF]
-
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling (RL Rec + CL)
arXiv 2024, [PDF]
-
Enhanced Generative Recommendation via Content and Collaboration Integration (Generative Rec + CL)
arXiv 2024, [PDF]
-
End-to-End Personalized Next Location Recommendation via Contrastive User Preference Modeling (POI Rec + CL)
arXiv 2023, [PDF]
-
Preference Aware Dual Contrastive Learning for Item Cold-Start Recommendation (Cold Start + CL)
AAAI 2024, [PDF]
-
Tail-STEAK: Improve Friend Recommendation for Tail Users via Self-Training Enhanced Knowledge Distillation (Friend Rec + CL)
-
Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation (Cross-Domain + CL)
-
Robust Federated Contrastive Recommender System against Model Poisoning Attack (Fed Rec + CL)
-
Bridging Language and Items for Retrieval and Recommendation (Multi Modal + CL)
-
DRepMRec: A Dual Representation Learning Framework for Multimodal Recommendation (Multi Modal + CL)
arXiv 2024, [PDF]
-
Knowledge-Aware Multi-Intent Contrastive Learning for Multi-Behavior Recommendation (Multi Behavior + CL)
arXiv 2024, [PDF]
-
General Item Representation Learning for Cold-start Content Recommendations (Cold Start + CL)
arXiv 2024, [PDF]
-
MARec: Metadata Alignment for Cold-start Recommendation (Cold Start + CL)
arXiv 2024, [PDF]
-
Contrastive Quantization based Semantic Code for Generative Recommendation (Generative Rec + CL)
CIKM 2023, [PDF]
-
Retrieval-Oriented Knowledge for Click-Through Rate Prediction (CTR + CL)
arXiv 2024, [PDF]