% Key papers for Robustness, privacy, and fairness of GNNs (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2020_gnnguard_59918,
  title = {{GNNGuard: Defending Graph Neural Networks against Adversarial Attacks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17522},
}

@inproceedings{aaai2023_let_4059,
  title = {{Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25558},
}

@inproceedings{iclr2020_efficient_29784,
  title = {{Efficient Probabilistic Logic Reasoning with Graph Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rJg76kStwH},
}

@inproceedings{neurips2021_be_61531,
  title = {{Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27501},
}

@inproceedings{neurips2020_reliable_60699,
  title = {{Reliable Graph Neural Networks via Robust Aggregation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18740},
}

@inproceedings{aaai2023_on_4273,
  title = {{On Generalized Degree Fairness in Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25574},
}

@inproceedings{aaai2023_extracting_3633,
  title = {{Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26232},
}

@inproceedings{aaai2024_fairsin_5960,
  title = {{FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28776},
}

@inproceedings{aaai2023_interpreting_3925,
  title = {{Interpreting Unfairness in Graph Neural Networks via Training Node Attribution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25905},
}

@inproceedings{iclr2022_understanding_31827,
  title = {{Understanding and Improving Graph Injection Attack by Promoting Unnoticeability}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6046},
}

@inproceedings{neurips2021_subgroup_61371,
  title = {{Subgroup Generalization and Fairness of Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27785},
}

@inproceedings{aaai2024_a_5067,
  title = {{A Simple and Yet Fairly Effective Defense for Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30098},
}

@inproceedings{cvpr2022_bandits_18348,
  title = {{Bandits for Structure Perturbation-Based Black-Box Attacks To Graph Neural Networks With Theoretical Guarantees}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2021_graph_686,
  title = {{Graph-Based Tri-Attention Network for Answer Ranking in CQA}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/14463-graph-based-tri-attention-network-for-answer-ranking-in-cqa/},
}

@inproceedings{aaai2021_adversarial_100,
  title = {{Adversarial Permutation Guided Node Representations for  Link Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09445-adversarial-permutation-guided-node-representations-for-link-prediction/},
}

@inproceedings{aaai2024_chasing_5395,
  title = {{Chasing Fairness in Graphs: A GNN Architecture Perspective}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30115},
}

@inproceedings{neurips2022_nas_65420,
  title = {{NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55694},
}

@inproceedings{aaai2021_uncertainty_1579,
  title = {{Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09524-uncertainty-matching-graph-neural-networks-to-defend-against-poisoning-attacks/},
}

@inproceedings{iclr2021_int_30253,
  title = {{INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2689},
}

@inproceedings{neurips2024_powergraph_74028,
  title = {{PowerGraph: A power grid benchmark dataset for graph neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97496},
}

@inproceedings{aaai2024_simcalib_7339,
  title = {{SimCalib: Graph Neural Network Calibration Based on Similarity between Nodes}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29450},
}

@inproceedings{aaai2025_erase_9008,
  title = {{Erase Then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33423},
}

@inproceedings{aaai2025_enhancing_8992,
  title = {{Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Training}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35425},
}

@inproceedings{aaai2025_k_9628,
  title = {{K-hop Hypergraph Neural Network: A Comprehensive Aggregation Approach}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35472},
}

@inproceedings{neurips2024_enhancing_70829,
  title = {{Enhancing Chess Reinforcement Learning with Graph Representation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96325},
}

@inproceedings{aaai2025_hyperdefender_9475,
  title = {{HyperDefender: A Robust Framework for Hyperbolic GNNs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34135},
}

@inproceedings{neurips2024_noisygl_72954,
  title = {{NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97611},
}

@inproceedings{aaai2025_community_8468,
  title = {{Community-Centric Graph Unlearning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34041},
}

@inproceedings{aaai2025_physics_10301,
  title = {{Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35025},
}

@inproceedings{cvpr2025_deterministic_25913,
  title = {{Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33664},
}

@inproceedings{neurips2024_gradient_72619,
  title = {{Gradient Rewiring for Editable Graph Neural Network Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94760},
}

@inproceedings{aaai2026_privacy_106269,
  title = {{Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38576},
}

@inproceedings{aaai2026_fairgse_106345,
  title = {{FairGSE: Fairness-Aware Graph Neural Network Without High False Positive Rates}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38652},
}

@inproceedings{aaai2024_identifying_6265,
  title = {{Identifying Guarantors of War Veterans Using Robust-SEAL: A Case of the Korean War}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30201},
}

@inproceedings{aaai2024_improving_6296,
  title = {{Improving GNN Calibration with Discriminative Ability: Insights and Strategies}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29082},
}

@inproceedings{aaai2025_fast_9149,
  title = {{Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33435},
}