3 papers
cs.CV2026
HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining
Juncheng Ma, Jianxin Bi, Yufan Deng +19
Embodied foundation models are expected to benefit from data scaling like large language models, but face a much tighter data bottleneck. Teleoperated real-robot trajectories remai…
cs.CV2026
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Yiyang Fu, Chubin Zhang, Shukai Gong +7
It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-Language-Action (VLA) models…
cs.LG2025
TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding
Shukai Gong, Yiyang Fu, Fengyuan Ran +2
We propose TPP-SD, a novel approach that accelerates Transformer temporal point process (TPP) sampling by adapting speculative decoding (SD) techniques from language models. By ide…