SOURCE-LINKED INTELLIGENCE
RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?
Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight into model reasoning under increasing spatial and procedural complexity. We introduce \textbf{RoboSPA} (\textbf{Robo}t \textbf{S}patial-\textbf{P}rocedural \textbf{A}ssessment), a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in VLA models. \texttt{RoboSPA} focuses on two core dimensions, Fine-Grained Spatial Reasonin
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T16:19:01.000Z
First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.