FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies

arXiv:2605.27284v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are increasingly expected to not only complete robot tasks, but also follow human instructions about how those tasks should be executed. However, existing robot datasets usually pair trajectories with coarse goal-level language, leaving execution-critical details such as active arm, approach direction, and contact region unspecified. This limits steerable policy learning and robotic video understanding. We introduce FineVLA, an open framework for action-aligned fine-grained VLA supervision. The framework incl

Source: arXiv cs.AI — read the full report at the original publisher.

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