| Explaining NLP Models via Minimal Contrastive Editing (MiCE) | Dec 27, 2020 | counterfactualMultiple-choice | CodeCode Available | 1 | 5 |
| Explaining Time Series via Contrastive and Locally Sparse Perturbations | Jan 16, 2024 | Contrastive Learningcounterfactual | CodeCode Available | 1 | 5 |
| A Structural Causal Model for MR Images of Multiple Sclerosis | Mar 4, 2021 | Causal Inferencecounterfactual | CodeCode Available | 1 | 5 |
| Counterfactual Explainable Recommendation | Aug 24, 2021 | Causal Inferencecounterfactual | CodeCode Available | 1 | 5 |
| Counterfactual Explanations for Neural Recommenders | May 11, 2021 | Collaborative Filteringcounterfactual | CodeCode Available | 1 | 5 |
| DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual Explanations | Nov 29, 2023 | counterfactualimage-classification | CodeCode Available | 1 | 5 |
| Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning | Jun 7, 2020 | counterfactualMulti-agent Reinforcement Learning | CodeCode Available | 1 | 5 |
| A Survey on Causal Inference for Recommendation | Mar 21, 2023 | Causal Inferencecounterfactual | CodeCode Available | 1 | 5 |
| A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges | Oct 21, 2022 | BenchmarkingCommunity Detection | CodeCode Available | 1 | 5 |
| Bias and Fairness in Large Language Models: A Survey | Sep 2, 2023 | counterfactualFairness | CodeCode Available | 1 | 5 |
