Author

Jin-Yu Zhang

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#artificial intelligence May 2026

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

FineVLA, an open framework for action-aligned fine-grained VLA supervision, is introduced and the largest real-world gains appear on pose, color, and approach direction, and approach direction--factors where goal-level instructions provide no guidance.

Xin-Tong Hu, Xuhong Huang, Jin-Yu Zhang et al. · arXiv.org · 4 citations

Preprint Aug 2026

$\tau_0$-VLA: a Hierarchical Robot Foundation Model with World-Model-Guided Test-Time Computation

Across in-domain and distribution-shifted settings, allocating additional test-time computation substantially improves next-subtask prediction accuracy, and these gains translate into higher closed-loop success on long-horizon robot manipulation tasks.

Xiaowei Cai, Yunuo Cai, Bing Chen et al. · 1 citation