Prior-minimal multi-agent RL agents develop indexical encoding, persistent self-state, and an echo-mismatch self-monitoring circuit that vanishes when the echo affordance is removed during training.
Aor: Anatomical ontology-guided reason- ing for medical large multimodal model in chest x-ray inter- pretation
2 Pith papers cite this work. Polarity classification is still indexing.
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Context alignment in medical VLMs raises AUC from 0.918 to 0.925, cuts hallucinated keywords from 1.14 to 0.25, shortens explanations to 15.3 words, and maintains calibrated uncertainty without raising model confidence.
citing papers explorer
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EasyLens: A Training-Free Plug-and-Play Subtle-Lesion Representation Amplifier for Medical Vision-Language Models
Prior-minimal multi-agent RL agents develop indexical encoding, persistent self-state, and an echo-mismatch self-monitoring circuit that vanishes when the echo affordance is removed during training.
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Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models
Context alignment in medical VLMs raises AUC from 0.918 to 0.925, cuts hallucinated keywords from 1.14 to 0.25, shortens explanations to 15.3 words, and maintains calibrated uncertainty without raising model confidence.