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Refresh timing, not just frequency, dictates Kronecker-preconditioned LLM training performance, with optimal placement flipping based on learning rate.
Current multimodal LLMs struggle with guideline-constrained clinical reasoning, but a simple multi-agent framework can significantly boost their performance on real-world lung cancer diagnosis and treatment.