Vision-language-action (VLA) models struggle to reuse recurring interactions in unseen tasks. Our diagnostic study reveals that reliable task completion does not imply consistent execution of constituent atomic actions across task contexts. We present LexiconVLA, a retrievable atomic-action lexicon for cross-task reuse...
Zeming Wei, Jian-Heng Ye, Xin-Shuai Song et al.· 0 citations
This work presents SkillSafetyBench, a runnable benchmark for evaluating skill-facing safety failures, and suggests that agent safety depends not only on model-level alignment, but also on how agents interpret skills, trust workflow context, and act through executable environments.
The streamlined, replay-free approach proves highly effective on a new continual learning benchmark and a practical path toward building prehensive, continually-learning medical VLMs and advancing the development of medical AI.
Hefei Li, Yuhui Zhang, Xiaohan Wang et al.· 0 citations
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