arXiv：cs.AI· Tu Nguyen, Matthieu Zimmer, Vu Anh Vu, Ziyi Wang, Jannik Hammel Nielsen, Xuebing Zhou, Haitham Bou Ammar·· 6 小时前AI 评分41
VICS-G：为 VLA 策略解码可行未来，而非仅安全动作
A Safe Action Is Not Enough: Feasible-Future Decoding for Vision-Language-Action Policies
AI 导读
针对冻结的视觉-语言-动作（VLA）策略只选局部安全动作、却可能断送安全完成任务路径的"可行性-似然性鸿沟"，研究者提出 alarm-triggered、免训练的 reranker VICS-G，通过选择性有限候选近似恢复最佳可行候选。
正文
Abstract:A safe action is not necessarily a viable one. A frozen vision-language-action (VLA) policy can favor a locally admissible move that leaves no policy-supported route to safe task completion. We call this the feasibility-likelihood gap: likelihood ranks the next move, while feasibility depends on the futures it leaves open.
To bring those futures into the decision, we derive the exact next-block marginal of the history-conditioned policy-environment trajectory law restricted to safe task completion. The derivation reveals a candidate-dependent feasible-future mass: its support records whether safe completion remains possible under the frozen continuation process, while its magnitude measures how much weighted safe-completion mass remains. Since exact evaluation is impractical online, we develop a selective finite-candidate approximation and establish conditions for recovering the best retained viable candidate.
Our alarm-triggered, training-free reranker VICS-G lowers mean cumulative safety cost by 1.9%-57.5% across six Safety-CHORES settings while remaining within 2.5 percentage points of policy sampling in success and 0.82 steps in mean episode length. Our approach offers a promising and practical path toward safer task completion, grounded in an exact policy-relative target yet requiring neither policy retraining nor online rollouts.
| Subjects: | Artificial Intelligence (cs.AI); Robotics (cs.RO) |
| Cite as: | arXiv:2610.05166 [cs.AI] |
| (or arXiv:2610.05166v2 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.05166 arXiv-issued DOI via DataCite |
Submission history
From: Tu Nguyen [view email]
[v1]
Sun, 4 Oct 2026 12:24:17 UTC (480 KB)
[v2]
Tue, 6 Oct 2026 10:17:30 UTC (480 KB)
来源：arXiv：cs.AI · arxiv.org