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How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation.

, , , , , and . CoRR, (2018)

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To Trust Or Not To Trust A Classifier., , and . CoRR, (2018)Interpreting Black Box Predictions using Fisher Kernels., , , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 3382-3390. PMLR, (2019)Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making., , , , , , , , , and 1 other author(s). CHI, page 4. ACM, (2019)On the Relationship Between Explanation and Prediction: A Causal View., , , , and . CoRR, (2022)Best of both worlds: local and global explanations with human-understandable concepts., , , , , , , , and . CoRR, (2021)Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016)., , and . CoRR, (2016)DISSECT: Disentangled Simultaneous Explanations via Concept Traversals., , , , , and . ICLR, OpenReview.net, (2022)Concept Bottleneck Models., , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 5338-5348. PMLR, (2020)Visualizing and Measuring the Geometry of BERT., , , , , , and . NeurIPS, page 8592-8600. (2019)The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification., , and . NIPS, page 1952-1960. (2014)