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Interpretability

173 directly classified papers

Papers per year

Papers

Initialization Noise in Image Gradients and Saliency Maps CVPR 2023
Assessing Word Importance Using Models Trained for Semantic Tasks ACL 2023
Investigating the Saliency of Sentiment Expressions in Aspect-Based Sentiment Analysis ACL 2023
Towards Robust Metrics for Concept Representation Evaluation AAAI 2023
Local Explanations for Reinforcement Learning AAAI 2023
Variable-Based Calibration for Machine Learning Classifiers AAAI 2023
Incorporating Attribution Importance for Improving Faithfulness Metrics ACL 2023
SketchXAI: A First Look at Explainability for Human Sketches CVPR 2023
On General Language Understanding EMNLP 2023
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder NIPS 2023
Use perturbations when learning from explanations NIPS 2023
Beyond Confidence: Reliable Models Should Also Consider Atypicality NIPS 2023
Emptying the Ocean with a Spoon: Should We Edit Models? EMNLP 2023
What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric ACL 2023
HINT: Hierarchical Neuron Concept Explainer CVPR 2022
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features JMLR 2022
Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees AISTATS 2022
Actionable Model-Centric Explanations (Student Abstract) AAAI 2022
AI Explainability 360: Impact and Design AAAI 2022
Optimal Local Explainer Aggregation for Interpretable Prediction AAAI 2022
Supervising Model Attention with Human Explanations for Robust Natural Language Inference AAAI 2022
Amortized Generation of Sequential Algorithmic Recourses for Black-Box Models AAAI 2022
Scaling Up Influence Functions AAAI 2022
Trading Complexity for Sparsity in Random Forest Explanations AAAI 2022
Interpretable Generative Adversarial Networks AAAI 2022