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Titlebook: AI-generated Content; First International Feng Zhao,Duoqian Miao Conference proceedings 2024 The Editor(s) (if applicable) and The Author(

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發(fā)表于 2025-3-28 15:46:48 | 只看該作者
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發(fā)表于 2025-3-28 21:12:09 | 只看該作者
978-981-99-7586-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
43#
發(fā)表于 2025-3-29 01:00:54 | 只看該作者
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發(fā)表于 2025-3-29 06:34:23 | 只看該作者
Advances in Intelligent and Soft Computingr noun phrases. In recent years, with the advancement of deep learning, the performance of anaphora resolution has significantly improved. To accurately identify the entities referred to by pronouns based on context, various factors need to be considered, such as the semantic dependencies in the con
45#
發(fā)表于 2025-3-29 09:36:17 | 只看該作者
Juan Wachs,Oren Shapira,Helman Sterns concerned with Chinese cultural subjects, Stable Diffusion needs to improve the quality of its results. This paper proposes a practical approach to address the challenges of utilizing popular AIGC (AI-Generated Content) technologies and integrating them into a cohesive system, which makes it easie
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發(fā)表于 2025-3-29 11:38:41 | 只看該作者
47#
發(fā)表于 2025-3-29 15:56:15 | 只看該作者
R. Ba?os,C. Gil,M.G. Montoya,J. Ortegaic illustrations, it still struggles to deliver predictable high-quality productions with multiple characters due to the interference of the text prompts. In this paper, we propose a practicable method to use ControlNet and stable diffusion to generate controllable outputs of multiple components. Th
48#
發(fā)表于 2025-3-29 21:51:49 | 只看該作者
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發(fā)表于 2025-3-30 00:24:28 | 只看該作者
Xolani B. Maxama,Elisha D. Markuscult to process and fully utilize such informative data. In recent years, Graph Neural Networks (GNNs) have achieved great success on learning representations for structural data. However, most of them are still considered as black boxes and the non-transparency of the models makes the explanation a
50#
發(fā)表于 2025-3-30 08:00:18 | 只看該作者
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