Showing 1 - 20 results of 6,838 for search '(( significant ((marked decrease) OR (largest decrease)) ) OR ( significant attention heads ))', query time: 1.16s Refine Results
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    Impact of attention head. by Xiaoye Lou (22470204)

    Published 2025
    “…To address the problems, this paper proposes an aspect-level sentiment analysis model (MSDC) based on multi-scale dual-channel feature fusion. First, through multi-head gated self-attention channels and graph neural network channels, the model further enhances its understanding of the spatial hierarchical structure of text data and improves the expressiveness of features. …”
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    Structure of multi-head self-attention. by DianGuo Cao (22486584)

    Published 2025
    “…In this study, we propose the SMMTM model, which combines spatiotemporal convolution (SC), multi-branch separable convolution (MSC), multi-head self-attention (MSA), temporal convolution network (TCN), and multimodal feature fusion (MFF). …”
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    Multi-head gated self-attention mechanism. by Xiaoye Lou (22470204)

    Published 2025
    “…To address the problems, this paper proposes an aspect-level sentiment analysis model (MSDC) based on multi-scale dual-channel feature fusion. First, through multi-head gated self-attention channels and graph neural network channels, the model further enhances its understanding of the spatial hierarchical structure of text data and improves the expressiveness of features. …”
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    Light multi-head self-attention. by Yandong Ru (18806183)

    Published 2024
    “…Meanwhile, this model employs a light multi-head attention mechanism module with an alternating structure, which can comprehensively extract multi-scale features while significantly reducing computational costs. …”
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    Multi-head self-attention module. by Yandong Ru (18806183)

    Published 2024
    “…Meanwhile, this model employs a light multi-head attention mechanism module with an alternating structure, which can comprehensively extract multi-scale features while significantly reducing computational costs. …”
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    Attention-LSTM performance. by Liang Chen (73736)

    Published 2025
    “…The research conclusively establishes that synergistic integration of adaptive signal processing and attention-based deep learning significantly advances PD diagnostics, achieving both computational efficiency and robust performance in complex operational environments.…”
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