local explanation

NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights AAAI 2022 SHAP-Based Explanation Methods: A Review for NLP Interpretability COLING 2022 Surrogate Model-Based Explainability Methods for Point Cloud NNs WACV 2022 Alibi Explain: Algorithms for Explaining Machine Learning Models JMLR 2021 An Analysis of LIME for Text Data AISTATS 2021 Learning Groupwise Explanations for Black-Box Models IJCAI 2021 Local Explanation of Dialogue Response Generation NeurIPS 2021 Local explanations via necessity and sufficiency: unifying theory and practice UAI 2021 On Guaranteed Optimal Robust Explanations for NLP Models IJCAI 2021 On Locality of Local Explanation Models NeurIPS 2021 Provably efficient, succinct, and precise explanations NeurIPS 2021 Learning Global Transparent Models consistent with Local Contrastive Explanations NeurIPS 2020 Model Agnostic Multilevel Explanations NeurIPS 2020 The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models EMNLP 2020 Building Human-Machine Trust via Interpretability AAAI 2019 Meaningful Explanations of Black Box AI Decision Systems AAAI 2019 What made you do this? Understanding black-box decisions with sufficient input subsets AISTATS 2019 Comparing Automatic and Human Evaluation of Local Explanations for Text Classification NAACL 2018 How much should you ask? On the question structure in QA systems. EMNLP 2018 Model Agnostic Supervised Local Explanations NeurIPS 2018