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| Learning to Bound Counterfactual Inference from Observational, Biased and Randomised Data | Dec 6, 2022 | counterfactualCounterfactual Inference | CodeCode Available | 0 |
| WatChat: Explaining perplexing programs by debugging mental models | Mar 8, 2024 | counterfactualLanguage Modelling | CodeCode Available | 0 |
| Counterfactual Explanations for Linear Optimization | May 24, 2024 | counterfactual | CodeCode Available | 0 |
| PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems | Nov 19, 2019 | counterfactualRecommendation Systems | CodeCode Available | 0 |
| Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations | Sep 27, 2022 | counterfactualDiversity | CodeCode Available | 0 |
| Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models | Oct 25, 2023 | counterfactual | CodeCode Available | 0 |
| Treble Counterfactual VLMs: A Causal Approach to Hallucination | Mar 8, 2025 | Autonomous Drivingcounterfactual | CodeCode Available | 0 |
| Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health | Oct 12, 2024 | counterfactualData Augmentation | CodeCode Available | 0 |
| FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles | Nov 27, 2019 | counterfactual | CodeCode Available | 0 |
