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The article introduces LearnActCoder, a role-aware error memory framework that adapts clinical coding agents by converting errors into structured lessons, improving CPT coding performance without model weight updates.
SwitchSD is an adaptive framework for speculative decoding in LLMs that uses intrinsic model signals to dynamically switch between neural drafting and context-based copying, achieving up to 15% throughput gains over baselines like EAGLE3.