{
  "id": 4063,
  "url": "https://arxiv.org/abs/2605.19294v2",
  "title": "DEFLECT: Temporal Counterfactual Preference Learning for Delay-Robust Asynchronous VLAs",
  "summary": "Vision-Language-Action (VLA) policies increasingly rely on asynchronous inference to hide large-model latency behind ongoing robot motion. While this avoids the stop-and-go behavior of synchronous action-chunk execution, it creates a prediction-execution mismatch: the next chunk is computed from a stale observation at inference start but executed only after the robot and scene have evolved. As a result, actions that fit the prediction-time state can become misaligned with the execution-time stat",
  "authors": "Yixiang Zhu, Yonghao Chen, Zijie Yang, Yusong Hu, Xinyu Chen",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-19T03:14:11.000Z",
  "fetched_at": "2026-07-14T16:30:45.935Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4063",
  "original_url": "https://arxiv.org/abs/2605.19294v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}