% Key papers for Causal approaches to fairness (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2018_fair_101469,
  title = {{Fair Inference on Outcomes}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11553},
}

@inproceedings{neurips2017_avoiding_56169,
  title = {{Avoiding Discrimination through Causal Reasoning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8861},
}

@inproceedings{cvpr2023_context_20639,
  title = {{Context De-Confounded Emotion Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/23278},
}

@inproceedings{neurips2020_long_60270,
  title = {{Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17315},
}

@inproceedings{aaai2021_counterfactual_335,
  title = {{Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08128-counterfactual-fairness-with-disentangled-causal-effect-variational-autoencoder/},
}

@inproceedings{icml2020_strategic_38803,
  title = {{Strategic Classification is Causal Modeling in Disguise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6779},
}

@inproceedings{neurips2018_equality_57100,
  title = {{Equality of Opportunity in Classification: A Causal Approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11367},
}

@inproceedings{cvpr2024_robust_24668,
  title = {{Robust Emotion Recognition in Context Debiasing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31329},
}

@inproceedings{neurips2021_decaf_62443,
  title = {{DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27552},
}

@inproceedings{aaai2022_training_2875,
  title = {{Training a Resilient Q-network against Observational Interference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08814-training-a-resilient-q-network-against-observational-interference/},
}

@inproceedings{aaai2023_improvement_3875,
  title = {{Improvement-Focused Causal Recourse (ICR)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26398},
}

@inproceedings{aaai2023_evaluating_3593,
  title = {{Evaluating Digital Agriculture Recommendations with Causal Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26697},
}

@inproceedings{aaai2022_unit_2911,
  title = {{Unit Selection with Causal Diagram}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05765-unit-selection-with-causal-diagram/},
}

@inproceedings{icml2022_causal_40318,
  title = {{Causal Conceptions of Fairness and their Consequences}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17121},
}

@inproceedings{neurips2022_debiased_66508,
  title = {{Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54364},
}

@inproceedings{icml2022_strategic_41210,
  title = {{Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16381},
}

@inproceedings{neurips2020_adversarial_59339,
  title = {{Adversarial Counterfactual Learning and Evaluation for Recommender System}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18467},
}

@inproceedings{icml2023_on_41870,
  title = {{On the Relationship Between Explanation and Prediction: A Causal View}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23810},
}

@inproceedings{neurips2022_performative_64777,
  title = {{Performative Power}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52858},
}

@inproceedings{neurips2024_a_73821,
  title = {{A hierarchical decomposition for explaining ML performance discrepancies}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93686},
}

@inproceedings{aaai2024_evaluating_5878,
  title = {{Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30239},
}

@inproceedings{neurips2025_unveiling_79246,
  title = {{Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=nOZSYSdzOP},
}

@inproceedings{aaai2026_uncovering_108956,
  title = {{Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/41308},
}

@inproceedings{neurips2025_performative_77026,
  title = {{Performative Validity of Recourse Explanations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=PhoyfQG9Vb},
}

@inproceedings{aaai2026_counterfactual_107409,
  title = {{Counterfactual Fairness with Imperfect Causal Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39761},
}

@inproceedings{iclr2024_interventional_34465,
  title = {{Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18609},
}

@inproceedings{icml2024_detecting_43470,
  title = {{Detecting and Identifying Selection Structure in Sequential Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34982},
}

@inproceedings{icml2025_fairpfn_46828,
  title = {{FairPFN: A Tabular Foundation Model for Causal Fairness}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45748},
}

@inproceedings{icml2025_counterfactual_48232,
  title = {{Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44380},
}

@inproceedings{icml2026_spurious_50992,
  title = {{Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Hpfybj9wkd},
}

@inproceedings{neurips2024_a_71884,
  title = {{A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95419},
}

@inproceedings{neurips2025_sample_77181,
  title = {{Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=RCXF0UEmuE},
}

@inproceedings{neurips2025_understanding_77767,
  title = {{Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=XOiZ9ydssl},
}

@inproceedings{neurips2025_causal_78116,
  title = {{Causal Explanation-Guided Learning for Organ Allocation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=b8XmjZmsN0},
}

@inproceedings{neurips2025_disentangling_78361,
  title = {{Disentangling misreporting from genuine adaptation in strategic settings: a causal approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=drmIBh6v2U},
}

@inproceedings{neurips2026_prediction_90649,
  title = {{Prediction-Intervention Games and Invariant Sets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151847},
}

@inproceedings{neurips2026_causality_91546,
  title = {{Causality can systematically address the monsters under the bench(marks)}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/140063},
}

@inproceedings{iclr2024_out_35705,
  title = {{Out-of-Variable Generalisation for Discriminative Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17368},
}