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Titlebook: AI and Multimodal Services– AIMS 2024; 13th International C Xiuqin Pan,Mengxing Huang,Liang-Jie Zhang Conference proceedings 2025 The Edito

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發(fā)表于 2025-3-23 13:25:16 | 只看該作者
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/167089.jpg
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發(fā)表于 2025-3-23 20:35:53 | 只看該作者
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發(fā)表于 2025-3-24 00:39:44 | 只看該作者
Steffen Hillebrecht,Anke-Andrea Peinigerce (AI) models limit their reliability for critical decisions. This paper proposes a paradigm shift from conventional data-driven to causal model-driven decision-making, leveraging advancements in causal inference and large language models (LLMs). By applying the capabilities of generative AI, this
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發(fā)表于 2025-3-24 03:55:21 | 只看該作者
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發(fā)表于 2025-3-24 10:07:00 | 只看該作者
Grundkurs Physik Band 2: Mechanik, yoga, which integrates physical, mental, and spiritual practices, has gained significant popularity. Correct yoga poses are crucial for achieving optimal results. Therefore, accurate recognition and classification of yoga poses are of great importance to practitioners..This paper introduces a nove
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發(fā)表于 2025-3-24 11:56:22 | 只看該作者
Grundkurs Physik Band 2: Mechanikels, such as T5, often fall short in producing diverse arguments, leading to a lack of depth and diversity in debate simulations. To address this, we developed a method integrating perspective features into the dataset and leveraging the pre-trained Mengzi-T5 model to generate compelling arguments f
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發(fā)表于 2025-3-24 16:33:34 | 只看該作者
,Ergebnisse pr?sentieren — das Referat,typically employ sequential encoding of features in a predetermined order, which results in imbalanced feature interactions between tasks, whereby information can only flow from the . clause encoder to the pair encoder. Additionally, the approach is not sensitive to long-distance ., and the relative
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發(fā)表于 2025-3-24 22:29:06 | 只看該作者
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發(fā)表于 2025-3-25 01:55:35 | 只看該作者
https://doi.org/10.1007/978-3-663-10209-0n that can provide insights into the system, but dealing with text feedback as unstructured data is difficult. This study utilizes advanced machine learning algorithms and statistics to enhance data quality and analyze customer feedback on Giao Hang Tiet Kiem services. Using a dataset of 12,624 cust
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