conftrace_

counterfactual explanation

139 papers

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CE

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explainable ai (480) model interpretability (519) algorithmic recourse (22) graph neural network (3962) generative model (2892) large language model (13587) text classification (6793) image classification (1944) causal inference (1630) explainable artificial intelligence (130)

Papers

On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective NIPS 2023
D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion NIPS 2023
Explaining Model Confidence Using Counterfactuals AAAI 2023
Formalising the Robustness of Counterfactual Explanations for Neural Networks AAAI 2023
Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models NIPS 2023
BayCon: Model-agnostic Bayesian Counterfactual Generator IJCAI 2022
Double Trouble: How to not Explain a Text Classifier’s Decisions Using Counterfactuals Synthesized by Masked Language Models? IJCNLP 2022
LIMREF: Local Interpretable Model Agnostic Rule-Based Explanations for Forecasting, with an Application to Electricity Smart Meter Data AAAI 2022
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles AAAI 2022
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis AISTATS 2022
CLEAR: Generative Counterfactual Explanations on Graphs NIPS 2022
CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs UAI 2022
Diffusion Visual Counterfactual Explanations NIPS 2022
Cycle-Consistent Counterfactuals by Latent Transformations CVPR 2022
Causal Explanations and XAI CLEAR 2022
Robust Counterfactual Explanations for Tree-Based Ensembles ICML 2022
Double Trouble: How to not Explain a Text Classifier’s Decisions Using Counterfactuals Synthesized by Masked Language Models? AACL 2022
Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees AISTATS 2022
A query-optimal algorithm for finding counterfactuals ICML 2022
Meaningfully debugging model mistakes using conceptual counterfactual explanations ICML 2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks AISTATS 2022
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates AAAI 2022
Machine Reading, Fast and Slow: When Do Models “Understand” Language? COLING 2022
ExSum: From Local Explanations to Model Understanding NAACL 2022
Attribution of predictive uncertainties in classification models UAI 2022