RoboSeed: Multidimensional Evaluation of Vision-Language-Action and World-Action Models
RoboSeed: Multidimensional Evaluation of Vision-Language-Action and World-Action Models: Capability, Resource Affordability, and Research Evidence
This paper presents RoboSeed, a framework for evaluating vision-language-action (VLA) and world-action models across five dimensions: capability, downstream training affordability, deployment affordability, locally verified research value, and reproduction evidence. The authors apply the framework to representative models to reveal budget-dependent backbone choices and sensitivity to adaptation recipes, while noting that incomplete serving traces prevent overall numerical rankings.
The authors introduce RoboSeed, a multidimensional evaluation framework for vision-language-action (VLA) and world-action models that assesses capability, resource affordability, and research evidence rather than relying solely on success rates.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
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arXiv:2610.40026v2 Announce Type: replace Abstract: Choosing a robot action model requires evidence about task capability, adaptation cost, deployment requirements, and the reliability of reported conclusions. Success rates alone offer limited guidance to researchers with different computing budgets and goals. We propose RoboSeed, a multidimensional evaluation framework for vision-language-action (VLA) and world-acti
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Source：arXiv Robotics — research abstracts · arxiv.org