Large Language Models (LLMs) have shown remarkable capabilities across diverse natural language processing tasks, from generating text to contextual reasoning. However, their efficiency is often hampered by the quadratic complexity of the self-attention mechanism. This challenge becomes particularly pronounced with longer input sequences, where computational and memory demands grow significantly. Traditional methods that modify self-attention […]
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