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: 8
- Only Data Augmentation Total Papers: 52
- Graph Models with CL Total Papers: 145
- Sequential Models with CL Total Papers: 118
- Other Tasks with CL Total Papers: 166
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Contrastive Self-supervised Learning in Recommender Systems: A Survey (Survey)
arXiv 2023, [PDF]
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Self-Supervised Learning for Recommender Systems A Survey (Survey + Framework)
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Self-Supervised Learning in Recommendation: Fundamentals and Advances (Tutorial)
WWW 2022, [Web]
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Tutorial: Self-Supervised Learning for Recommendation: Foundations, Methods and Prospects (Tutorial)
DASFAA 2023, [Web]
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SSLRec: A Self-Supervised Learning Framework for Recommendation (Framework)
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A Comprehensive Survey on Self-Supervised Learning for Recommendation (Survey)
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Towards Graph Contrastive Learning: A Survey and Beyond (Survey)
arXiv 2024, [PDF]
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Data Augmentation for Sequential Recommendation: A Survey (Survey)
arXiv 2024, [PDF]
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Enhancing Collaborative Filtering with Generative Augmentation (CF + GAN + DA)
KDD 2019, [PDF]
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Future Data Helps Training Modeling Future Contexts for Session-based Recommendation (Session + DA)
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Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer (Sequential + DA)
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Self-Knowledge Distillation with Bidirectional Chronological Augmentation of Transformer for Sequential Recommendation (Sequential + DA)
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Counterfactual Data-Augmented Sequential Recommendation (Sequential + Counterfactual + DA)
SIGIR 2021, [PDF]
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CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation (Sequential + Counterfactual + DA)
SIGIR 2021, [PDF]
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Effective and Efficient Training for Sequential Recommendation using Recency Sampling (Sequential + DA)
RecSys 2022, [PDF]
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Data Augmentation Strategies for Improving Sequential Recommender Systems (Sequential + DA)
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Learning to Augment for Casual User Recommendation (Sequential + DA)
WWW 2022, [PDF]
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Recency Dropout for Recurrent Recommender Systems (RNN + DA)
arXiv 2022, [PDF]
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Improved Recurrent Neural Networks for Session-based Recommendations (RNN + DA)
DLRS 2016, [PDF]
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Bootstrapping User and Item Representations for One-Class Collaborative Filtering (CF + Graph + DA)
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MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems (Graph + DA)
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Improving Recommendation Fairness via Data Augmentation (Fairness + DA)
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Fairly Adaptive Negative Sampling for Recommendations (Fairness + DA)
WWW 2023, [PDF]
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Creating Synthetic Datasets for Collaborative Filtering Recommender Systems using Generative Adversarial Networks (CF + DA)
arXiv 2023, [PDF]
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Graph Collaborative Signals Denoising and Augmentation for Recommendation (CF + DA)
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Data Augmented Sequential Recommendation based on Counterfactual Thinking (Sequential + DA)
TKDE 2022, [PDF]
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Multi-Epoch Learning for Deep Click-Through Rate Prediction Models (CRT + DA)
arXiv 2023, [PDF]
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Improving Conversational Recommendation Systems via Counterfactual Data Simulation (Conversational Rec + DA)
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Disentangled Variational Auto-encoder Enhanced by Counterfactual Data for Debiasing Recommendation (Debias Rec + DA)
arXiv 2023, [PDF]
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Domain Disentanglement with Interpolative Data Augmentation for Dual-Target Cross-Domain Recommendation (Cross-Domain + DA)
RecSys 2023, [PDF]
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Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions (Session + DA)
RecSys 2023, [PDF]
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Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation (RL Rec + DA)
arXiv 2022, [PDF]
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Augmented Negative Sampling for Collaborative Filtering (CF + DA)
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gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Sequential + DA)
RecSys 2023, [PDF]
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Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation (DA)
arXiv 2023, [PDF]
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Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems (Graph + DA)
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Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation (Graph + DA)
arXiv 2023, [PDF]
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Diffusion Augmentation for Sequential Recommendation (Sequential + DA)
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Large Language Models as Data Augmenters for Cold-Start Item Recommendation (DA)
WWW 2024, [PDF]
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SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation (Sequential + DA)
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CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation (DA)
arXiv 2024, [PDF]
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ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation (DA)
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Repeated Padding for Sequential Recommendation (Sequential + DA)
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Rethinking sequential relationships: Improving sequential recommenders with inter-sequence data augmentation (Sequential + DA)
amazon.science 2024, [PDF]
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Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation (POI Rec + DA)
TOIS 2024, [PDF]
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TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation (POI Rec + DA)
AAAI 2024, [PDF]
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Improving Long-Tail Item Recommendation with Graph Augmentation (Graph + DA)
CIKM 2023, [PDF]
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Improving Long-Tail Item Recommendation with Graph Augmentation (Coupon Rec + DA)
WWW 2024, [PDF]
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Dataset Regeneration for Sequential Recommendation (Sequential + DA)
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Counterfactual Data Augmentation for Debiased Coupon Recommendations Based on Potential Knowledge (DA)
WWW 2024, [PDF]
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A Generic Behavior-Aware Data Augmentation Framework for Sequential Recommendation (Sequential + DA)
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Cross-reconstructed Augmentation for Dual-target Cross-domain Recommendation (Cross-Domain + DA)
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SCM4SR: Structural Causal Model-based Data Augmentation for Robust Session-based Recommendation (Session Rec + DA)
SIGIR 2024, [PDF]
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GenRec: A Flexible Data Generator for Recommendations (DA)
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Sample Enrichment via Temporary Operations on Subsequences for Sequential Recommendation (Sequential + DA)
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Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation (POI Rec + DA)
IJCAI 2021, [PDF]
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Federated Recommender System Based on Diffusion Augmentation and Guided Denoising (Fed Rec + DA)
TOIS 2024, [PDF]
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Sliding Window Training - Utilizing Historical Recommender Systems Data for Foundation Models (Sequential + DA)
RecSys 2024, [PDF]
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PACIFIC: Enhancing Sequential Recommendation via Preference-aware Causal Intervention and Counterfactual Data Augmentation (Sequential + DA)
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Guided Diffusion-based Counterfactual Augmentation for Robust Session-based Recommendation (Session + DA)
RecSys 2024, [PDF]
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Self-supervised Graph Learning for Recommendation (Graph + CL + DA)
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Contrastive Graph Structure Learning via Information Bottleneck for Recommendation (Graph + CL)
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Are graph augmentations necessary? simple graph contrastive learning for recommendation (Graph + CL)
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XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation (Graph + CL)
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Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation (Graph + CL + DA)
arXiv 2022, [PDF]
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DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation (POI Rec, Graph + CL + DA)
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An MLP-based Algorithm for Efficient Contrastive Graph Recommendations (Graph + CL + DA)
SIGIR 2022, [PDF]
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A Review-aware Graph Contrastive Learning Framework for Recommendation (Graph + CL + DA)
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Simple Yet Effective Graph Contrastive Learning for Recommendation (Graph + CL + DA)
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Contrastive Meta Learning with Behavior Multiplicity for Recommendation (Graph + CL + DA)
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Disentangled Contrastive Learning for Social Recommendation (Graph + CL + DA)
CIKM 2022, [PDF]
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Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning (Graph + CL)
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Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System (Graph + CL)
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Knowledge Graph Contrastive Learning for Recommendation (Graph + DA + CL)
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Temporal Knowledge Graph Reasoning with Historical Contrastive Learning (Graph + CL)
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Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation (Graph + SSL)
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SAIL: Self-Augmented Graph Contrastive Learning (Graph + CL)
AAAI 2022, [PDF]
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Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
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Socially-Aware Self-Supervised Tri-Training for Recommendation (Graph + CL)
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Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
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Multi-Behavior Dynamic Contrastive Learning for Recommendation (Graph + CL)
arXiv 2022, [PDF]
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Self-Augmented Recommendation with Hypergraph Contrastive Collaborative Filtering (Graph + CL)
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Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning (Graph + CF + CL)
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Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation (Graph + CL)
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Hypergraph Contrastive Collaborative Filtering (Graph + CF + CL + DA)
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Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems (Graph + CL)
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Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation (Group Rec, Graph + CL + DA)
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Self-Supervised Hypergraph Transformer for Recommender Systems (Graph + SSL)
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Episodes Discovery Recommendation with Multi-Source Augmentations (Graph + DA + CL)
arXiv 2023, [PDF]
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Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation (Graph + Sequential + CL)
TOIS 2023, [PDF]
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Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation (Graph + DA + CL)
DASFAA 2023, [PDF]
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SimCGNN: Simple Contrastive Graph Neural Network for Session-based Recommendation (Graph + CL)
arXiv 2023, [PDF]
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MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning (Graph + DA + CL)
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Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation (Graph + Session + CL)
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Self-Supervised Graph Co-Training for Session-based Recommendation (Graph + Session + CL)
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Heterogeneous Graph Contrastive Learning for Recommendation (Graph + CL)
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Automated Self-Supervised Learning for Recommendation (Graph + DA + CL)
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Graph-less Collaborative Filtering (Graph + CL)
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Disentangled Contrastive Collaborative Filtering (Graph + CL)
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Knowledge-refined Denoising Network for Robust Recommendation (Graph + CL)
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Disentangled Graph Contrastive Learning for Review-based Recommendation (Graph + CL)
IJCAI 2023, [PDF]
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Adaptive Graph Contrastive Learning for Recommendation (Graph + CL)
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Knowledge Enhancement for Contrastive Multi-Behavior Recommendation (Graph + CL)
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Contrastive Meta Learning with Behavior Multiplicity for Recommendation (Graph + CL)
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Graph Transformer for Recommendation (Graph + CL)
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PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation (Graph + CL)
CIKM 2023, [PDF]
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Knowledge Graph Self-Supervised Rationalization for Recommendation (Graph + CL)
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Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization (Graph + CL)
SIGIR 2021, [PDF]
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Generative-Contrastive Graph Learning for Recommendation (Graph + CL)
SIGIR 2023, [PDF]
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AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering (Graph + CL)
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Candidate–aware Graph Contrastive Learning for Recommendation (Graph + CL)
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Multi-View Graph Convolutional Network for Multimedia Recommendation (Graph + CL)
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Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation (Graph + CL)
SIGIR 2023, [PDF]
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uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering (Graph + CL)
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Contrastive Box Embedding for Collaborative Reasoning (Graph + CL)
SIGIR 2023, [PDF]
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Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph (Graph + CL)
CIKM 2023, [PDF]
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Contrastive Graph Prompt-tuning for Cross-domain Recommendation (Graph + CL)
arXiv 2023, [PDF]
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Dual Intents Graph Modeling for User-centric Group Discovery (Graph + CL)
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Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning (Graph + CL)
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Multi-Relational Contrastive Learning for Recommendation (Graph + CL)
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Multi-behavior Recommendation with SVD Graph Neural Networks (Graph + CL)
arXiv 2023, [PDF]
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E-commerce Search via Content Collaborative Graph Neural Network (Graph + DA + CL)
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Long-tail Augmented Graph Contrastive Learning for Recommendation (Graph + DA + CL)
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LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning (Graph + CL)
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On the Sweet Spot of Contrastive Views for Knowledge-enhanced Recommendation (Graph + CL)
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Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering (Graph + CL)
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Towards Robust Neural Graph Collaborative Filtering via Structure Denoising and Embedding Perturbation (Graph + CL)
TOIS 2023, [PDF]
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TDCGL: Two-Level Debiased Contrastive Graph Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
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Topology-aware Debiased Self-supervised Graph Learning for Recommendation (Graph + CL)
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Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering (Graph + DA + CL)
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Contrastive Multi-Level Graph Neural Networks for Session-based Recommendation (Graph + CL)
TMM 2023, [PDF]
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An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations (Graph + CL)
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An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations (Graph + CL)
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Denoised Self-Augmented Learning for Social Recommendation (Graph + CL)
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Intent-aware Recommendation via Disentangled Graph Contrastive Learning (Graph + CL)
IJCAI 2023, [PDF]
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GENET: Unleashing the Power of Side Information for Recommendation via Hypergraph Pre-training (Graph + CL)
arXiv 2023, [PDF]
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Graph Pre-training and Prompt Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
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Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning (Graph + CL)
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ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation (Graph + Multi-Modal + CL)
arXiv 2023, [PDF]
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Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems (Graph + LLM + CL)
arXiv 2023, [PDF]
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LGMRec: Local and Global Graph Learning for Multimodal Recommendation (Graph + Multi-Modal + CL)
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RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation (Graph + CL)
arXiv 2023, [PDF]
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DiffKG: Knowledge Graph Diffusion Model for Recommendation (Graph + CL)
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QoS-Aware Graph Contrastive Learning for Web Service Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Challenging Low Homophily in Social Recommendation (Graph + CL)
WWW 2024, [PDF]
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RecDCL: Dual Contrastive Learning for Recommendation (Graph + CL)
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Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course Recommendation (Graph + CL)
TKDD 2024, [PDF]
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Graph Contrastive Learning With Negative Propagation for Recommendation (Graph + CL)
TCSS 2024, [PDF]
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General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout (Graph + CL)
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Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph (Graph + CL)
arXiv 2024, [PDF]
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FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling (Graph + CL)
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Self-supervised Contrastive Learning for Implicit Collaborative Filtering (Graph + DA + CL)
arXiv 2024, [PDF]
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Dual-Channel Multiplex Graph Neural Networks for Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Bilateral Unsymmetrical Graph Contrastive Learning for Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Knowledge-aware Dual-side Attribute-enhanced Recommendation (Graph + CL)
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A Progressively-Passing-then-Disentangling Approach to Recipe Recommendation (Graph + CL)
TMM 2024, [PDF]
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Graph Augmentation for Recommendation (Graph + DA + CL)
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One Backpropagation in Two Tower Recommendation Models (Graph + CL)
arXiv 2024, [PDF]
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Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users (Graph + CL)
COLING 2024, [PDF]
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Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations (Graph + Social Rec + CL)
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Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation (Graph + CL)
AAAI 2024, [PDF]
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A Directional Diffusion Graph Transformer for Recommendation (Graph + CL)
SIGIR 2024, [PDF]
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Heterogeneous Adaptive Preference Learning for Recommendation (Graph + CL)
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Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Diversification-Enhancing Contrastive Learning (Graph + CL)
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Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation (Graph + CL)
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Enhanced Hierarchical Contrastive Learning for Recommendation (Graph + CL)
AAAI 2024, [PDF]
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How to Improve Representation Alignment and Uniformity in Graph-based Collaborative Filtering? (Graph + CL)
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PopDCL: Popularity-aware Debiased Contrastive Loss for Collaborative Filtering (Graph + CL)
CIKM 2023, [PDF]
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Improving Graph Collaborative Filtering with Directional Behavior Enhanced Contrastive Learning (Graph + CL)
TKDD 2024, [PDF]
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Stochastic Sampling for Contrastive Views and Hard Negative Samples in Graph-based Collaborative Filtering (Graph + CL)
arXiv 2024, [PDF]
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Learning Social Graph for Inactive User Recommendation (Graph + CL)
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Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering (Graph + CL)
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Graph Contrastive Learning with Kernel Dependence Maximization for Social Recommendation (Graph + CL)
WWW 2024, [PDF]
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MvStHgL: Multi-view Hypergraph Learning with Spatial-temporal Periodic Interests for Next POI Recommendation (Graph + POI Rec + CL)
TOIS 2024, [PDF]
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A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation (Graph + CL)
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Knowledge Enhanced Multi-intent Transformer Network for Recommendation (Graph + CL)
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QAGCF: Graph Collaborative Filtering for Q&A Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Balancing Embedding Spectrum for Recommendation (Graph + CL)
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Meta Graph Learning for Long-tail Recommendation (Graph + CL)
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Heterogeneous Hypergraph Embedding for Recommendation Systems (Graph + CL)
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Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations (Graph + CL)
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Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning (Graph + CL)
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Graph Augmentation Empowered Contrastive Learning for Recommendation (Graph + DA + CL)
TOIS 2024, [PDF]
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L2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering (Graph + CL)
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RevGNN: Negative Sampling Enhanced Contrastive Graph Learning for Academic Reviewer Recommendation (Graph + CL)
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Intent-Guided Heterogeneous Graph Contrastive Learning for Recommendation (Graph + CL)
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Your Graph Recommender is Provably a Single-view Graph Contrastive Learning (Graph + CL)
arXiv 2024, [PDF]
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High-Order Fusion Graph Contrastive Learning for Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Feedback Reciprocal Graph Collaborative Filtering (Graph + CL)
CIKM 2024, [PDF]
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Symmetric Graph Contrastive Learning against Noisy Views for Recommendation (Graph + CL)
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Dual-Channel Latent Factor Analysis Enhanced Graph Contrastive Learning for Recommendation (Graph + DA + CL)
arXiv 2024, [PDF]
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Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering (Graph + DA + CL)
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Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks (Graph + Attack + CL)
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Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation (Graph + CL)
arXiv 2024, [PDF]
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Multi-view Hypergraph-based Contrastive Learning Model for Cold-Start Micro-video Recommendation (Graph + CL)
arXiv 2024, [PDF]
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TwinCL: A Twin Graph Contrastive Learning Model for Collaborative Filtering (Graph + CL)
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Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation (Graph + CL)
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Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation (Graph + CL)
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Adaptive Fusion of Multi-View for Graph Contrastive Recommendation (Graph + DA + CL)
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Simplify to the Limit! Embedding-less Graph Collaborative Filtering for Recommender Systems (Graph + CL)
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FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning (Graph + DA + CL)
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Decoupled Behavior-based Contrastive Recommendation (Graph + CL)
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Mixed Supervised Graph Contrastive Learning for Recommendation (Graph + DA + CL)
arXiv 2024, [PDF]
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Bi-Level Graph Structure Learning for Next POI Recommendation (Graph + POI Rec + CL)
TKDE 2024, [PDF]
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Bi-Level Graph Structure Learning for Next POI Recommendation (Graph + Multi-Modal + CL)
arXiv 2024, [PDF]
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Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation (Sequential + CL + DA)
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Contrastive Learning for Sequential Recommendation (Sequential + CL + DA)
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Contrastive Self-supervised Sequential Recommendation with Robust Augmentation (Sequential + CL + DA)
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Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation (Sequential + CL + DA)
arXiv 2022, [PDF]
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S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization (Sequential + CL + DA)
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Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation (Sequential + CL + DA)
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Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation (Sequential + CL + DA)
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Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation (Sequential + CL + DA)
ICDM 2021, [PDF]
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Contrastive Learning with Bidirectional Transformers for Sequential Recommendation (Sequential + CL + DA)
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ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation (Sequential + CL + DA)
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Temporal Contrastive Pre-Training for Sequential Recommendation (Sequential + CL + DA)
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Multi-level Contrastive Learning Framework for Sequential Recommendation (Graph + Sequential + CL)
CIKM 2022, [PDF]
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Equivariant Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
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Explanation Guided Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
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Intent Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
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Dual Contrastive Network for Sequential Recommendation (Sequential + CL)
SIGIR 2022, [PDF]
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Dual Contrastive Network for Sequential Recommendation with User and Item-Centric Perspectives (Sequential + CL)
arXiv 2022, [PDF]
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Enhancing Sequential Recommendation with Graph Contrastive Learning (Sequential + Graph + CL + DA)
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Disentangling Long and Short-Term Interests for Recommendation (Sequential + Graph + CL)
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Hyperbolic Hypergraphs for Sequential Recommendation (Sequential + Graph + CL + DA)
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Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation (Sequential + CL)
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Dual-interest Factorization-heads Attention for Sequential Recommendation (Sequential + CL)
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GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation (Sequential + DA + CL)
arXiv 2023, [PDF]
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Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation (Sequential + CL)
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A Self-Correcting Sequential Recommender (Sequential + DA + SSL)
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User Retention-oriented Recommendation with Decision Transformer (Sequential + CL)
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Debiased Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
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Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders (Sequential + CL)
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Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning (Multi-Modal + Sequential + CL)
arXiv 2023, [PDF]
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Sequential Recommendation with Diffusion Models (Diffsion + Sequential + CL)
arXiv 2023, [PDF]
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Triple Sequence Learning for Cross-domain Recommendation (Sequential + CL)
arXiv 2023, [PDF]
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Contrastive Cross-Domain Sequential Recommendation (Cross-Domain + Sequential + CL)
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Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation (VAE + Sequential + CL)
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Meta-optimized Contrastive Learning for Sequential Recommendation (Meta + Sequential + CL)
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Frequency Enhanced Hybrid Attention Network for Sequential Recommendation (Sequential + CL)
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Self-Supervised Multi-Modal Sequential Recommendation (Multi-Moda + Sequential + CL)
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Conditional Denoising Diffusion for Sequential Recommendation (Diffusion + Sequential + CL)
arXiv 2023, [PDF]
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Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation (Diffusion + Sequential + CL)
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Multi-view Multi-behavior Contrastive Learning in Recommendation (Sequential + Graph + CL)
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Denoising Multi-modal Sequential Recommenders with Contrastive Learning (Sequential + CL)
arXiv 2023, [PDF]
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Multi-view Multi-behavior Contrastive Learning in Recommendation (Sequential + Graph + CL)
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Contrastive Enhanced Slide Filter Mixer for Sequential Recommendation (Sequential + CL)
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Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems (Sequential + DA + CL)
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When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation (Sequential + CL)
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Text Is All You Need: Learning Language Representations for Sequential Recommendation (Sequential + CL)
KDD 2023, [PDF]
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Sequential Recommendation with Multiple Contrast Signals (Sequential + CL)
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Robust Reinforcement Learning Objectives for Sequential Recommender Systems (Sequential + CL)
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AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation (Sequential + CL)
PMLR 2023, [PDF]
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Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation (Sequential + CL)
PMLR 2023, [PDF]
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Hierarchical Contrastive Learning with Multiple Augmentation for Sequential Recommendation (Sequential + DA + CL)
arXiv 2023, [PDF]
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Poisoning Self-supervised Learning Based Sequential Recommendations (Sequential + Attack + DA + CL)
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Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation (Sequential + CL)
SIGIR 2023, [PDF]
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Leveraging Negative Signals with Self-Attention for Sequential Music Recommendation (Sequential + CL)
RecSys 2023, [PDF]
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RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendationn (Sequential + DA + CL)
CIKM 2023, [PDF]
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FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning (Sequential + DA + CL)
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Unbiased and Robust: External Attention-enhanced Graph Contrastive Learning for Cross-domain Sequential Recommendation (Sequential + Graph + DA + CL)
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Dual-Scale Interest Extraction Framework with Self-Supervision for Sequential Recommendation (Sequential + CL)
arXiv 2023, [PDF]
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Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation (Sequential + DA + CL)
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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]
-
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)
-
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]
-
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation (Sequential + LLM + CL)
arXiv 2024, [PDF]
-
ID-centric Pre-training for Recommendation (Sequential + CL)
arXiv 2024, [PDF]
-
Diffusion-based Contrastive Learning for Sequential Recommendation (Sequential + DA + CL)
arXiv 2024, [PDF]
-
Soft Contrastive Sequential Recommendation (Sequential + DA + CL)
TOIS 2024, [PDF]
-
Modeling User Fatigue for Sequential Recommendation (Sequential + DA + CL)
-
Aligned Side Information Fusion Method for Sequential Recommendation (Sequential + CL)
WWW 2024, [PDF]
-
Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation (Sequential + CL)
-
SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation (Sequential + Graph + CL)
-
Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation (Sequential + CL)
-
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender System (Sequential + CL)
arXiv 2024, [PDF]
-
Pacer and Runner: Cooperative Learning Framework between Single- and Cross-Domain Sequential Recommendation (Sequential + CL)
-
Scaling Sequential Recommendation Models with Transformers (Sequential + CL)
-
CMCLRec: Cross-modal Contrastive Learning for User Cold-start Sequential Recommendation (Sequential + CL)
SIGIR 2024, [PDF]
-
Multimodal Pre-training for Sequential Recommendation via Contrastive Learning (Sequential + CL)
TORS 2024, [PDF]
-
Beyond Inter-Item Relations: Dynamic Adaptive Mixture-of-Experts for LLM-Based Sequential Recommendation (Sequential + LLM + CL)
arXiv 2024, [PDF]
-
Contrastive Learning on Medical Intents for Sequential Prescription Recommendation (Sequential + CL)
-
Disentangled Multi-interest Representation Learning for Sequential Recommendation (Sequential + CL)
KDD 2024, [PDF]
-
Multi-intent Aware Contrastive Learning for Sequential Recommendation (Sequential + CL)
arXiv 2024, [PDF]
-
Large Language Model Empowered Embedding Generator for Sequential Recommendation (Sequential + LLM + CL)
-
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services (Sequential + LLM + CL)
arXiv 2024, [PDF]
-
Sequential Recommendation with Collaborative Explanation via Mutual Information Maximization (Sequential + CL)
-
Intent-Enhanced Data Augmentation for Sequential Recommendation (Sequential + DA + CL)
-
Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Sample Selection (Sequential + CL)
-
Context Matters: Enhancing Sequential Recommendation with Context-aware Diffusion-based Contrastive Learning (Sequential + CL)
-
Momentum Contrastive Bidirectional Encoding with Self-Distillation for Sequential Recommendation (Sequential + CL)
CIKM 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]
-
Contrastive Learning for Conversion Rate Prediction (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]
-
Denoising Long-and Short-term Interests for Sequential Recommendation (Session + DA + CL)
-
Learnable Tokenizer for LLM-based Generative Recommendation (Gen Rec + CL)
arXiv 2024, [PDF]
-
MVBIND: Self-Supervised Music Recommendation For Videos Via Embedding Space Binding (Music Rec + CL)
arXiv 2024, [PDF]
-
CELA: Cost-Efficient Language Model Alignment for CTR Prediction (LLM + CTR + CL)
arXiv 2024, [PDF]
-
A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce (Search & Rec + CL)
SIGIR 2024, [PDF]
-
Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation (Concept Rec + CL)
arXiv 2024, [PDF]
-
Bilateral Multi-Behavior Modeling for Reciprocal Recommendation in Online Recruitment (Job Rec + CL)
TKDE 2024, [PDF]
-
Multi-Modal Recommendation Unlearning (Rec Unlearning + CL)
arXiv 2024, [PDF]
-
Your decision path does matter in pre-training industrial recommenders with multi-source behaviors (Cross-Domain + CL)
arXiv 2024, [PDF]
-
NoteLLM-2: Multimodal Large Representation Models for Recommendation (Multi-Modal + CL)
arXiv 2024, [PDF]
-
Multimodality Invariant Learning for Multimedia-Based New Item Recommendation (Multi-Modal + CL)
-
Cross-Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction (CTR + CL)
arXiv 2024, [PDF]
-
Medication Recommendation via Dual Molecular Modalities and Multi-Substructure Distillation (Med Rec + CL)
arXiv 2024, [PDF]
-
Item-Language Model for Conversational Recommendation (Conversational Rec + CL)
arXiv 2024, [PDF]
-
Boosting Multimedia Recommendation via Separate Generic and Unique Awareness (Multi-Modal + CL)
-
Contextual Distillation Model for Diversified Recommendation (Diversified Rec + CL)
KDD 2024, [PDF]
-
DiffMM: Multi-Modal Diffusion Model for Recommendation (Multi-Modal + DA + CL)
-
Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback (Multi-Modal + CL)
-
EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration (Gen Rec + CL)
KDD 2024, [PDF]
-
Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learning (LLM Rec + CL)
arXiv 2024, [PDF]
-
Hyperbolic Knowledge Transfer in Cross-Domain Recommendation System (Cross-Domain + CL)
arXiv 2024, [PDF]
-
MMBee: Live Streaming Gift-Sending Recommendations via Multi-Modal Fusion and Behaviour Expansion (Gift-Sending Rec + CL)
KDD 2024, [PDF]
-
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning (Job Rec + CL)
KDD 2024, [PDF]
-
Personalised Outfit Recommendation via History-aware Transformers (Outfit Rec + CL)
arXiv 2024, [PDF]
-
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation (Search & Rec + CL)
-
Language Models Encode Collaborative Signals in Recommendation (LLM + Graph + CL)
-
GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation (Multi-Modal + CL)
-
A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation (Multi-Modal + CL)
arXiv 2024, [PDF]
-
MOSAIC: Multimodal Multistakeholder-aware Visual Art Recommendation (Art Rec + CL)
arXiv 2024, [PDF]
-
Disentangled Contrastive Hypergraph Learning for Next POI Recommendation (POI Rec + DA + CL)
-
Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation (CTR + CL)
-
SimCEN: Simple Contrast-enhanced Network for CTR Prediction (CTR + CL)
-
CETN: Contrast-enhanced Through Network for Click-Through Rate Prediction (CTR + CL)
-
Multi-task Heterogeneous Graph Learning on Electronic Health Records (Drug Rec + CL)
-
Don’t Click the Bait: Title Debiasing News Recommendation via Cross-Field Contrastive Learning (News Rec + CL)
arXiv 2024, [PDF]
-
EasyRec: Simple yet Effective Language Models for Recommendation (LLM + CL)
-
Bundle Recommendation with Item-level Causation-enhanced Multi-view Learning (Bundle Rec + CL)
arXiv 2024, [PDF]
-
Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems (Debias + CL)
arXiv 2024, [PDF]
-
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding (CTR + LLM + CL)
RecSys 2024, [PDF]
-
Topic Modeling as Multi-Objective Contrastive Optimization (CTR + LLM + CL)
ICLR 2024, [PDF]
-
Contrastive Learning for Neural Topic Model (NTM + CL)
-
Improving Multimodal Sentiment Analysis: Supervised Angular Margin-based Contrastive Learning for Enhanced Fusion Representation (Margin + CL)
EMNLP 2023, [PDF]
-
Meta-optimized Angular Margin Contrastive Framework for Video-Language Representation Learning (Margin + CL)
ECCV 2024, [PDF]
-
Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions (Adaptive + CL)
-
KDMCSE: Knowledge Distillation Multimodal Sentence Embeddings with Adaptive Angular margin Contrastive Learning (Margin + CL)
NAACL 2024, [PDF]
-
Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation (Cross-Domain + Fed Rec + CL)
-
Mitigating Negative Transfer in Cross-Domain Recommendation via Knowledge Transferability Enhancement (Cross-Domain + CL)
KDD 2024, [PDF]
-
Federated Prototype-based Contrastive Learning for Privacy-Preserving Cross-domain Recommendation (Cross-Domain + CL)
arXiv 2024, [PDF]
-
A Unified Framework for Cross-Domain Recommendation (Cross-Domain + CL)
arXiv 2024, [PDF]
-
End-to-End Learnable Item Tokenization for Generative Recommendation (Gen Rec + CL)
arXiv 2024, [PDF]
-
Towards Leveraging Contrastively Pretrained Neural Audio Embeddings for Recommender Tasks (Music Rec + CL)
RecSys 2024, [PDF]
-
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios (Multi-Modal + CL)
-
The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective (Cross-Domain + CL)
CIKM 2024, [PDF]
-
Contrastive Clustering Learning for Multi-Behavior Recommendation (Multi-Behavior + CL)
-
End-to-End Learnable Item Tokenization for Generative Recommendation (Gen Rec + CL)
-
Improving Object Detection via Local-global Contrastive Learning (OD + CL)
-
DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation (Job Rec + CL)
-
Neural Contrast: Leveraging Generative Editing for Graphic Design Recommendations (Design Rec + CL)
PRICAI 2024, [PDF]
-
Pseudo Dataset Generation for Out-of-domain Multi-Camera View Recommendation (View Rec + CL)
arXiv 2024, [PDF]
-
Hyperbolic Contrastive Learning for Cross-Domain Recommendation (Cross-Domain + CL)
-
Enhancing CTR prediction in Recommendation Domain with Search Query Representation (CTR + CL)
CIKM 2024, [PDF]
-
Multi-Modal Correction Network for Recommendation (Multi-Modal + CL)
TKDE 2024, [PDF]