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When discussing the improvement of LLM accuracy, the concept of entropy is inescapable. The introduction of the attention mechanism enabled models to dynamically extract high-information elements from the entire input. This mirrors entropy minimization in communication channels—achieving the most efficient transfer of information. By concentrating information on key tokens, filtering out noise, and isolating the semantic core, LLMs perform a kind of optimized encoding and decoding that closely resembles human-like thought processes.