Self-supervised learning for recommender systems: A survey

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Momentum Contrast for Unsupervised Visual Representation Learning

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Graph Attention Networks

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Matrix Factorization Techniques for Recommender Systems

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A Comprehensive Survey on Graph Neural Networks

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Representation Learning with Contrastive Predictive Coding

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Curriculum learning

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LightGCN

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Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

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Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

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ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

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Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

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Wide & Deep Learning for Recommender Systems

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Deep Neural Networks for YouTube Recommendations

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Self-Attentive Sequential Recommendation

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BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

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Introduction to Recommender Systems Handbook

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Deep Interest Network for Click-Through Rate Prediction

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Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

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Learning deep representations by mutual information estimation and maximization

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Self-supervised Learning: Generative or Contrastive

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Deep Learning Based Recommender System

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Self-supervised Graph Learning for Recommendation

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Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts

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f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

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Tri-training: exploiting unlabeled data using three classifiers

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Collaborative Denoising Auto-Encoders for Top-N Recommender Systems

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S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization

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GCC

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Contrastive Learning for Sequential Recommendation

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Bias and Debias in Recommender System: A Survey and Future Directions

Chen, J., Dong, H., Wang, X., Feng, F., Wang, M., & He, X. (2023) · ACM Transactions on Information Systems · doi:10.1145/3564284 · Cited by 741 · see citing works

Understanding the Behaviour of Contrastive Loss

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Are Graph Augmentations Necessary?

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Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

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Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

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Prototypical Contrastive Learning of Unsupervised Representations

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Graph Self-Supervised Learning: A Survey

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Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation

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Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)

Geng, S., Liu, S., Fu, Z., Ge, Y., & Zhang, Y. (2022) · Proceedings of the 16th ACM Conference on Recommender Systems · doi:10.1145/3523227.3546767 · Cited by 556 · see citing works

Knowledge Graph Contrastive Learning for Recommendation

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RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

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GPT-GNN

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Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation

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Hypergraph Contrastive Collaborative Filtering

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Intent Contrastive Learning for Sequential Recommendation

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Self-Supervised Learning of Graph Neural Networks: A Unified Review

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Data augmentation approaches in natural language processing: A survey

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XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation

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Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive

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Contrastive Learning for Cold-Start Recommendation

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Challenging the long tail recommendation

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Towards Universal Sequence Representation Learning for Recommender Systems

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Pre-training of Graph Augmented Transformers for Medication Recommendation

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Self-supervised Learning for Large-scale Item Recommendations

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Self-Supervised Learning for Multimedia Recommendation

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Data Augmentation for Deep Graph Learning

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Disentangled Self-Supervision in Sequential Recommenders

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Self-Supervised Reinforcement Learning for Recommender Systems

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A Survey on Adversarial Recommender Systems

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Socially-Aware Self-Supervised Tri-Training for Recommendation

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Social Influence-Based Group Representation Learning for Group Recommendation

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BiNE

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MixGCF

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Enhancing Social Recommendation With Adversarial Graph Convolutional Networks

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Self-Supervised Graph Co-Training for Session-based Recommendation

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Empowering News Recommendation with Pre-trained Language Models

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Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders

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Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation

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Fast-adapting and privacy-preserving federated recommender system

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The World is Binary: Contrastive Learning for Denoising Next Basket Recommendation

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Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems

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Self-supervised Pretraining of Visual Features in the Wild

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Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer

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Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation

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Bipartite Graph Embedding via Mutual Information Maximization

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On the Effectiveness of Sampled Softmax Loss for Item Recommendation

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Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation

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Bootstrapping User and Item Representations for One-Class Collaborative Filtering

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Collaborative User Network Embedding for Social Recommender Systems

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Social Recommendation with Self-Supervised Metagraph Informax Network

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Try This Instead

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Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization

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U-BERT: Pre-training User Representations for Improved Recommendation

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Contrastive Cross-domain Recommendation in Matching

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Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices

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SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

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GroupIM

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Enhancing Collaborative Filtering with Generative Augmentation

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UNBERT: User-News Matching BERT for News Recommendation

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Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation

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Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation

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Backdoor Attacks on Self-Supervised Learning

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Pre-training Graph Transformer with Multimodal Side Information for Recommendation

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Recommender systems based on generative adversarial networks: A problem-driven perspective

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Contrastive Self-supervised Sequential Recommendation with Robust AugmentationPreprint

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Joint Modeling of Users' Interests and Mobility Patterns for Point-of-Interest Recommendation

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Heterogeneous Graph Contrastive Learning Network for Personalized Micro-Video Recommendation

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Spatio-Temporal Recommendation in Social Media

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Hyperbolic Hypergraphs for Sequential Recommendation

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Gray-Box Shilling Attack: An Adversarial Learning Approach

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