Collection of the SOTA fairness and robustness research articles in recommender systems.
A curated list of paper on fairness and robustness in recommender systems.
Papers are sorted by their uploaded dates in descending order.
Search keywords like conference name (e.g., NeurIPS
), task name (e.g., Link Prediction
), model name (e.g., DeepWalk
), or method name (e.g., Robust
) over the webpage to quickly locate related papers.
Fairness papers sorted by year: | 2022 | 2021 | 2020 | 2019 |
Robustness papers sorted by year: | 2022 | 2021 | 2020 | 2019 |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2022 | Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage | Graph | Graph Classification | GNNs | KDD’2022 | Link | Link |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2022 | A Comprehensive Survey on Trustworthy Recommender Systems | Survey | Trustworthy Recommendeation | None | arXiv | Link | |
2022 | A survey for trust-aware recommender systems: A deep learning perspective | Survey | Trustworthy Recommendeation | Knowledge-Based Systems'2022 | Link | ||
2022 | A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks | Survey | Adversarial Recommender Systems | ACM Computing Surveys | Link | ||
2022 | A Survey on Trustworthy Recommender Systems | Survey | Recommendeation | arXiv | Link | ||
2022 | Adversarial Graph Perturbations for Recommendations at Scale | Adversarial Training | Defend Against Adversarial Attacks | GNNs | SIGIR'22 | Link | |
2022 | Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering | Graph denoising and diversity preserving | Recommendeation | GNN-based CF | SIGIR'22 | Link | |
2022 | Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack Perspective | Masked Targeted Topologica Attack | Attack on GNN-CF | GNN-based CF | arXiv | Link | |
2022 | Self-Supervised Hypergraph Transformer for Recommender Systems | Self-Supervised Graph Learning | Alleviating the data sparsity and noise issues | GNN-based CF | KDD'2022 | Link | Link |
2022 | Shilling Black-box Recommender Systems by Learning to Generate Fake User Profiles | GAN | Shilling attack on black-box RS | WRMF... | TNNLS'2022 | Link | Link |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2021 | Bias and Debias in Recommender System: A Survey and Future Directions | Survey | Recommendeation | None | arXiv | Link | |
2021 | Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation | Graph Denoise, Similarity | Recommendeation, Denoise | GNNs | arXiv | Link | |
2021 | Denoising Implicit Feedback for Recommendation | Adaptive Denoising Training, Loss | Recommendeation, Denoise | MF | WSDM '21 | Link | |
2021 | Multi-view Denoising Graph Auto-Encoders on Heterogeneous Information Networks for Cold-start Recommendation | Multi-View Denoising Graph Auto-Encoders | Cold-start Recommendeation, Denoise | GNNs | KDD '21 | Link | |
2021 | Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack | Shilling Attack, GAN | Attack | GCN-based RS | Information Sciences'2021 | Link | |
2021 | Self-supervised Graph Learning for Recommendation | Self-supervised Graph Learning (SGL) | Allievate long-tail item and noisy interaction | LightGCN | SIGIR'2022 | Link | Link |
2021 | Self-supervised Learning for Large-scale Item Recommendations | Self-Supervised Learning (SSL) | Allievate highly-skewed data distribution, lack of explicit user feedback problems | Two-tower DNN | CIKM'2021 | Link |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2020 | Enhancing Social Recommendation with Adversarial Graph Convolutional Networks | GCN-based autoencoder,adversarial training | Social Recommendation | GNNs | TKDE'2020 | Link | |
2020 | GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection | Detection | Recommendation | GCN | SIGIR'2020 | Link | Link |
2020 | Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback | Prune structure of interaction graph by similarity of multiple modalities | Multimedia Recommendation, Denoise | GCN | SIGIR'2020 | Link | Link |
2020 | Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective | Survey | Recommendeation based on GAN | arXiv | Link | ||
2020 | Revisiting Adversarially Learned Injection Attacks Against Recommender Systems | Attack | Adversarial Injection Attack | WRMF,NCF,multi-vae,CML,ItemCF | Recsys'2020 | Link | Link |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2019 | Adversarial Collaborative Neural Network for Robust Recommendation | Adversarial Training | Recommendation | Neural Network(NN)-based recommendation | SIGIR'2019 | Link | |
2019 | Collaborative Generative Adversarial Network for Recommendation Systems | GAN | Recommendation | DNN | ICDEW'2019 | Link | Link |
2019 | Generating Reliable Friends via Adversarial Training to Improve Social Recommendation | GAN | Social Recommendation | MF | ICDM'2019 | Link | Link |
Year | Title | Type | Target Task | Target Model | Venue | Paper | Code |
---|---|---|---|---|---|---|---|
2018 | Adversarial Personalized Ranking for Recommendation | Adversarial Training | Recommendation | DNN | SIGIR'2018 | Link | Link |
2018 | Attentive Contextual Denoising Autoencoder for Recommendation | Denoising Autoencoders | Recommendation, Denoising | ICTIR'2018 | Link | Link | |
2018 | Link Prediction Adversarial Attack | Attack in link prediction | Link prediction | GAE,DeepWalk,node2Vec... | Arvix | Link | Link |
2018 | Poisoning Attacks to Graph-Based Recommender Systems | Poisoning Attack | Graph-based RS | Graph-based RS | ACSAC'2018 | Link |