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Titlebook: Artificial Intelligence; Third CAAI Internati Lu Fang,Jian Pei,Ruiping Wang Conference proceedings 2024 The Editor(s) (if applicable) and T

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發(fā)表于 2025-3-30 08:58:02 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162061.jpg
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發(fā)表于 2025-3-30 15:18:33 | 只看該作者
Hans van Haut,Heinrich Stratmannto recognize that not all samples are treated unfairly, resulting in data heterogeneity in fair machine learning. Existing fair models primarily focus on achieving fairness across all heterogeneous data, yet they often fall short in ensuring fairness within specific subgroups, such as fairly treated
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H.-W. Radeke,N. Jaeger,J. Vogel,L. Weissbachniques, AI-based image generation has been applied to various fields. However, AI Generated Images (AIGIs) may have some unique distortions compared to natural images, thus many generated images are not qualified for real-world applications. Consequently, it is important and significant to study sub
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發(fā)表于 2025-3-31 09:19:43 | 只看該作者
R. Gerlach,J. Hannappel,B. Heinrichs,M. Grawes a great memory footprint and computing time when processing a long decoding sequence. To solve this problem, we propose a model named time-sparse transducer, which introduces a time-sparse mechanism into transducer. In this mechanism, we obtain the intermediate representations by reducing the tim
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