| Explaining Explanations: An Overview of Interpretability of Machine Learning | May 31, 2018 | BIG-bench Machine LearningExplainable Artificial Intelligence (XAI) | CodeCode Available | 0 |
| How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees | Jun 22, 2020 | BIG-bench Machine LearningDecision Making | CodeCode Available | 0 |
| A Causal Framework to Measure and Mitigate Non-binary Treatment Discrimination | Mar 28, 2025 | Binary Classificationcounterfactual | CodeCode Available | 0 |
| Unsupervised bias discovery in medical image segmentation | Sep 1, 2023 | FairnessImage Segmentation | CodeCode Available | 0 |
| Explaining Neural Networks with Reasons | May 20, 2025 | Fairness | CodeCode Available | 0 |
| Montague semantics and modifier consistency measurement in neural language models | Oct 10, 2022 | Fairness | CodeCode Available | 0 |
| "Explain it in the Same Way!" -- Model-Agnostic Group Fairness of Counterfactual Explanations | Nov 27, 2022 | counterfactualDecision Making | CodeCode Available | 0 |
| How Far Can It Go?: On Intrinsic Gender Bias Mitigation for Text Classification | Jan 30, 2023 | Fairnesstext-classification | CodeCode Available | 0 |
| Explanation-Guided Fairness Testing through Genetic Algorithm | May 16, 2022 | AttributeFairness | CodeCode Available | 0 |
| Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model | May 18, 2023 | FairnessMachine Translation | CodeCode Available | 0 |
