4 papers
ATHENA: Accelerated Multi-Task Heterogeneous Influence Functions for Robot Data Curation
Tao Xu, Jiaxin Wang, Runhao Zhang +7
In robot imitation learning, influence functions provide a principled approach to quantify each demonstration's effect on robot task outcomes, yet scaling them to billion-parameter…
Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols
Xianchao Zeng, Xinyu Zhou, Youcheng Li +5
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic manipulation, yet they remain limited in failure diagnosis and learning from failures. Add…
The Great March 100: 100 Detail-oriented Tasks for Evaluating Embodied AI Agents
Ziyu Wang, Chenyuan Liu, Yushun Xiang +16
Recently, with the rapid development of robot learning and imitation learning, numerous datasets and methods have emerged. However, these datasets and their task designs often lack…
L1 Sample Flow for Efficient Visuomotor Learning
Weixi Song, Zhetao Chen, Tao Xu +6
Denoising-based models, such as diffusion and flow matching, have been a critical component of robotic manipulation for their strong distribution-fitting and scaling capacity. Conc…