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Attention mechanisms form the core of transformers, enabling them to capture dependencies across input sequences. This chapter defines self-attention and multi-head attention, explores their mathematical properties, and discusses variations like cross-attention and efficient attention mechanisms, emphasizing scalability and interpretability.

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Attention Mechanisms: Theory and Variations

  • 章节

  • 发表日期：

    2025年

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  • Pradeep Singh,
  • Balasubramanian Raman

摘要

Attention mechanisms form the core of transformers, enabling them to capture dependencies across input sequences. This chapter defines self-attention and multi-head attention, explores their mathematical properties, and discusses variations like cross-attention and efficient attention mechanisms, emphasizing scalability and interpretability.