Deciphering the Attention Mechanism: Towards a Max-Margin Solution in Transformer Models

The attention mechanism has played a significant role in natural language processing and large language models. The attention mechanism allows the transformer decoder to focus on the most relevant parts of the input sequence. It plays a crucial role by computing softmax similarities among input tokens and serves as the foundational framework of the architecture. […]

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attention computing decoder editors pick focus language language models language processing large language large language models max natural natural language natural language processing processing role softmax solution staff tokens transformer transformer decoder transformer models