← Back to Benchmarks
simmediummanipulation-datametric · varies
RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning
Description
Synthetic data generated by video generative models has shown promise for robot learning as a scalable pipeline, but it often suffers from inconsistent action quality due to imperfectly generated videos. Recently, vision-language models (VLMs) have been leveraged to validate video quality, but they have limitations in distinguishing physically accurate videos and, even then, cannot directly evaluate the generated actions themselves. To tackle this issue, we introduce RoboCurate, a novel syntheti