{
  "id": 3737,
  "url": "https://arxiv.org/abs/2605.25829v1",
  "title": "OASIS: Observation-Action Space Alignment via SE(3) Trajectory Prediction for Robotic Manipulation",
  "summary": "Recent vision-language-action (VLA) models and world action models (WAMs) advance robotic manipulation by enriching intermediate representations with auxiliary spatial features or future visual-state prediction. However, these representations largely remain within the observation space and do not share the rigid-body geometry of the action space, forcing the action decoder to implicitly recover this geometry. We propose OASIS, a visuomotor policy that aligns the intermediate representation with ",
  "authors": "Xinzhe Chen, Sihua Ren, Liqi Huang, Haowen Sun, Mingyang Li, Xingyu Chen et al.",
  "category": "research",
  "topics": "regulation,safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-25T13:28:33.000Z",
  "fetched_at": "2026-07-14T16:30:27.611Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3737",
  "original_url": "https://arxiv.org/abs/2605.25829v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}