{
  "id": 14417,
  "url": "https://arxiv.org/abs/2607.26055v1",
  "title": "$π\\mathbf{R}^2$: Reactive Real-time Flow Policies",
  "summary": "Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretrained backbones. Such chunks run open-loop, so the policy cannot react to sensory input arriving mid-execution, sacrificing \\emph{reactivity}. Replanning more often would restore it, but the perception-to-action pipeline (a large backbone plus multiple denoising steps) is too slow: this \\emph{latency} forbids frequent replanning and leaves committed actions stale, making such policies",
  "authors": "Sungjae Park, Shubham Tulsiani",
  "category": "research",
  "topics": "regulation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-28T17:59:31.000Z",
  "fetched_at": "2026-07-29T05:10:12.205Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/14417",
  "original_url": "https://arxiv.org/abs/2607.26055v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}