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Beyond Appearance Shifts: Task-Semantic Action Calibration for VLA Models

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still lack a clear mechanism to balance behavioral stability with task-semantic sensitivity. We identify two complementary failure modes. Under task-preserving changes, where task semantics remain unchanged but scene appearance varies (e.g., style, illumination, clutter, or paraphrasing), policies often exhibit unnecessary action drift. Conversely, under semantic-breaking changes, where key task semantics such as the target object or constraint are altered, policies frequently fail to produce suf

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First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.