MedVerse structures medical reasoning as a Petri-net DAG for parallel LLM execution, delivering up to 8.9% gains on general models plus 1.3x lower latency and 1.7x higher throughput versus specialized medical LLMs.
arXiv preprint arXiv:2508.02258 (2025)
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MedSynapse-V proposes a latent diagnostic memory evolution framework using Meta Query, Causal Counterfactual Refinement, and Intrinsic Memory Transition to improve medical VLM diagnostic accuracy over chain-of-thought methods.
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MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution
MedVerse structures medical reasoning as a Petri-net DAG for parallel LLM execution, delivering up to 8.9% gains on general models plus 1.3x lower latency and 1.7x higher throughput versus specialized medical LLMs.
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MedSynapse-V: Bridging Visual Perception and Clinical Intuition via Latent Memory Evolution
MedSynapse-V proposes a latent diagnostic memory evolution framework using Meta Query, Causal Counterfactual Refinement, and Intrinsic Memory Transition to improve medical VLM diagnostic accuracy over chain-of-thought methods.