4. 原聡@第12回最先端NLP勉強会
XAI技術がユーザの役に立つか調べた研究(一部)
n arXivの論文
[1] Manipulating and Measuring Model Interpretability, arXiv’18.
[2] Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Term Performance, arXiv’20.
n NLP系の会議論文
[3] Comparing Automatic and Human Evaluation of_Local Explanations for Text Classification, NAACL-HLT’18.
[4] Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?, ACL’20.
n CV系の会議論文
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n FAT系の会議論文
[5] On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception
Detection, FAT*’19.
[6] Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making, FAT*’20.
n HCI系の会議論文
[7] The Effects of Example-Based Explanations in a Machine Learning Interface, IUI’19.
[8] What can AI do for me? Evaluating Machine Learning Interpretations in Cooperative Play, IUI’19.
[9] Effects of Influence on User Trust in Predictive Decision Making, CHI’19.
[10] The Principles and Limits of Algorithm-in-the-Loop Decision Making, CSCW’19.
[11] “Why is ‘Chicago’ deceptive?” Towards Building Model-Driven Tutorial for Humans, CHI’20.
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