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StarVLA-$\alpha$: Reducing Complexity in Vision-Language-Action Systems

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学术前沿 5.5 分 — 中等偏上:有一定信息增量和参考价值
原文: cs.AI updates on arXiv.org

评分 5.5 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等偏上:有一定信息增量和参考价值

StarVLA-$\alpha$: Reducing Complexity in Vision-Language-Action Systems

arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landscape remains highly fragmented and complex: as existing approaches vary substantially in architectures, training data, embodiment configurations, and benchmark-specific engineering. In this work, we introduce StarVLA-$\alpha$, a simple yet strong baseline designed to study VLA design choices under…