{
  "id": 7158,
  "url": "https://arxiv.org/abs/2603.15797v2",
  "title": "OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning",
  "summary": "Large Language Models (LLMs) have demonstrated exceptional logical reasoning capabilities but frequently struggle with the continuous spatiotemporal dynamics governed by Partial Differential Equations (PDEs), often resulting in non-physical hallucinations. Existing approaches typically resort to costly, domain-specific fine-tuning, which severely limits cross-domain generalization and interpretability. To bridge this gap, we propose OMNIFLOW, a neuro-symbolic architecture designed to ground froz",
  "authors": "Hao Wu, Yongheng Zhang, Yuan Gao, Fan Xu, Fan Zhang, Ruobing Xie et al.",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-16T18:29:01.000Z",
  "fetched_at": "2026-07-14T16:32:59.168Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7158",
  "original_url": "https://arxiv.org/abs/2603.15797v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}