{
  "id": 14539,
  "url": "https://arxiv.org/abs/2607.25108",
  "title": "OPERA: Offline Policy-guided Expert Routing and Adaptation for Universal Biomedical Image Analysis",
  "summary": "Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, protocols, and patient populations. High-performing models consequently require repeated domain-specific fine-tuning, which is a costly cycle that becomes impractical when labels are scarce or privacy constraints limit data sharing. We propose OPERA (Offline Policy-guided Expert Routing and Adaptation), a multi-agent ensemble framework that addresses",
  "authors": "Zihan Li, Feiyang Liu, Dandan Shan, Ruibo Wang, Qingqi Hong",
  "category": "research",
  "topics": "regulation,privacy-surveillance,healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-26T20:00:00.000Z",
  "fetched_at": "2026-07-30T05:10:24.387Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/14539",
  "original_url": "https://arxiv.org/abs/2607.25108",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}