内部 发表于 2025-3-23 13:43:23
Adding Why to What? Analyses of an Everyday Explanationfrom a video recall to explore how Explainers (EX) justified their explanation. We found that EX were focusing on the physical aspects of the game first (Architecture) and only later on aspects of the Relevance. Reasoning in the video recalls indicated that EX regarded the focus on the Architecturecrease 发表于 2025-3-23 17:09:58
http://reply.papertrans.cn/32/3193/319287/319287_12.pngobjection 发表于 2025-3-23 18:29:13
The Importance of Distrust in AIto prevent both disuse of these systems as well as overtrust. From our analysis of research on interpersonal trust, trust in automation, and trust in (X)AI, we identify the potential merit of the distinction between trust and distrust (in AI). We propose that alongside trust a healthy amount of distungainly 发表于 2025-3-23 23:08:13
Leveraging Group Contrastive Explanations for Handling Fairnesssights through a comprehensive explanation of the decision-making process, enabling businesses to: detect the presence of direct discrimination on the target variable and choose the most appropriate fairness framework.Generator 发表于 2025-3-24 02:51:02
Handbook of Phenomenological Aesthetics problem-solving strategies. Additionally, by inspecting the attention weights layer by layer, we uncover an unconventional finding that layer 10, rather than the model’s final layer, is the optimal layer to unfreeze for the least parameter-intensive approach to fine-tune the model. We support theseFUME 发表于 2025-3-24 09:31:46
http://reply.papertrans.cn/32/3193/319287/319287_16.pngJOG 发表于 2025-3-24 14:09:32
http://reply.papertrans.cn/32/3193/319287/319287_17.pngTAG 发表于 2025-3-24 18:52:11
http://reply.papertrans.cn/32/3193/319287/319287_18.png微枝末节 发表于 2025-3-24 22:10:19
http://reply.papertrans.cn/32/3193/319287/319287_19.png洞穴 发表于 2025-3-25 01:37:30
Handbook of Philosophical Logicdata features effectively. Experimental results on industrial datasets demonstrate that the proposed method outperforms existing baselines and achieves state-of-the-art performance. The proposed approach offers a promising solution for accurate and interpretable spatio-temporal data forecasting.