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The Evolution of Attention in Large Language Models: Mechanisms, Trade-offs, and Emerging Trends
Self-attention gives LLMs fine-grained, query-dependent access to context, but dense token interactions incur quadratic prefill cost and a key--value cache growing with context length. Research thus spans explicit-memory compression, sparse access, recurrent state construction, structured state dyna
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