HUMP
发表于 2025-3-28 15:10:17
Injazz J. Chen,Kenneth A. Paetschiscriminative than descriptions produced by existing captioning methods. In this work, we emphasize the importance of producing an explanation for an observed action, which could be applied to a black-box decision agent, akin to what one human produces when asked to explain the actions of a second h
啜泣
发表于 2025-3-28 20:56:31
Daniel R. Williams,Norman McIntyrerowd-sourced human evaluation indicates that our ensemble visual explanation is significantly qualitatively outperform each of the individual system’s visual explanation. Overall, our ensemble explanation is better 61. of the time when compared to any individual system’s explanation and is also suff
过剩
发表于 2025-3-29 01:22:47
Ahu Yazici Ayyildiz,Erdogan Kocons actually influence the output. This produces more succinct visual explanations and more accurately exposes the network’s behavior. We demonstrate the effectiveness of our model on three datasets totaling 16 h of driving. We first show that training with attention does not degrade the performance
epidermis
发表于 2025-3-29 04:35:44
Derek L. Milne,Robert P. Reiserf a data-driven job candidate assessment system, intended to be explainable towards non-technical hiring specialists. In connection to this, we also give an overview of more traditional job candidate assessment approaches, and discuss considerations for optimizing the acceptability of technology-sup
agenda
发表于 2025-3-29 09:08:18
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