{
  "id": 17176453,
  "title": "Aligning Medical Vision Language Models at the Capability Boundary with Entropy Adaptive Rubric Grounding",
  "url": "https://urgent.news/2026/10/29/aligning-medical-vision-language-models-at-the-capability-boundary",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-29T11:15:12.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.39835v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "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…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}