arXiv Machine Learning July 30, 2026 By Iok Tong Lei, Ying Jie Yap, Wei Huang, Qingchen Xie, Qianzhi Li, Yujie Zhang, Xiaolong Liu, Zhidong Deng

Teaching Tiny VLA Models Where to Look and How to Move

Read the original on arXiv Machine Learning →

arXiv:2607. 04171v3 Announce Type: replace-cross Abstract: Tiny Vision-Language-Action models are appealing for real-time robotic control, but reducing model scale often weakens two capabilities essential for manipulation: task-conditioned spatial grounding and coherent action generation.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control

From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data

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