AI RESEARCH
See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs
arXiv CS.LG
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ArXi:2606.02735v1 Announce Type: cross Generalization remains a central bottleneck for vision-language-action (VLA) models: under distractors, appearance shifts, and semantically similar tasks, the policy must often infer local execution details from coarse instructions while also deciding which parts of the image matter for control. We present S2 (See Less, Specify More), a framework for improving VLA generalization by