别名 发表于 2025-3-30 08:50:57
Power, Politics, and the Civil Sphereing post-hoc explanations, however, they fail to make the model itself more interpretable. To fill this gap, we introduce the Concept Distillation Module, the first differentiable concept-distillation approach for graph networks. The proposed approach is a layer that can be plugged into any graph ne宽大 发表于 2025-3-30 15:04:10
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http://reply.papertrans.cn/32/3193/319287/319287_53.pngintoxicate 发表于 2025-3-30 22:15:32
http://reply.papertrans.cn/32/3193/319287/319287_54.pnghidebound 发表于 2025-3-31 02:23:33
Hassan Namazi,Mohsen Mosadegh,Mozhgan Hayasiot (in- or out-of-distribution) to the ones the ML system has been trained on may lead to potentially fatal consequences. Operational data compliance with the training data has to be verified by the data analyst, who must also understand, in operation, if the autonomous decision-making is still safeGREEN 发表于 2025-3-31 05:48:09
Popular Narratives of the Cochlear Implantnot discriminate against specific groups of people becomes crucial. Reaching this objective requires a multidisciplinary approach that includes domain experts, data scientists, philosophers, and legal experts, to ensure complete accountability for algorithmic decisions. In such a context, Explainabl溺爱 发表于 2025-3-31 11:50:23
978-3-031-44069-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl砍伐 发表于 2025-3-31 14:06:19
Explainable Artificial Intelligence978-3-031-44070-0Series ISSN 1865-0929 Series E-ISSN 1865-0937LIMN 发表于 2025-3-31 20:54:02
https://doi.org/10.1007/978-3-031-44070-0artificial intelligence; interpretable machine learning; causal inference & explanations; argumentativeEnervate 发表于 2025-4-1 00:03:09
Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models e recent advancements in pre-trained language models based on transformers and their increasing integration into daily life, addressing this issue has become more pressing. In order to achieve an explainable AI model, it is essential to comprehend the procedural steps involved and compare them with