Aligning Medical Vision Language Models at the Capability Boundary with Entropy Adaptive Rubric Grounding
arXiv:2610.39835v1 Announce Type: cross Abstract: Medical diagnostic reasoning requires verifiable links between visual evidence and clinical knowledge, yet current medical vision language models are aligned with objectives that reward the wrong behavior. Uniform supervised fine tuning lets easy cases dominate updates while clinically critical boundary cases saturate prematurely. Sparse rewards based only on final-answer correctness cannot assess anatomical grounding or clinical logic, inviting…