2 citations · 2 across the 14 of their papers we have counts for
4 papers · 1 filter
Robo-Dopamine: General Process Reward Modeling for High-Precision Robotic Manipulation
Huajie Tan, Sixiang Chen, Yijie Xu +12
The primary obstacle for applying reinforcement learning (RL) to real-world robotics is the design of effective reward functions. While recently learning-based Process Reward Model…
AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation
Sixiang Chen, Jiaming Liu, Siyuan Qian +9
Recently, mobile manipulation has attracted increasing attention for enabling language-conditioned robotic control in household tasks. However, existing methods still face challeng…
FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning
Jiajun Cao, Qizhe Zhang, Peidong Jia +11
Vision-Language-Action (VLA) models have demonstrated significant potential in complex scene understanding and action reasoning, leading to their increasing adoption in end-to-end…
HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model
Jiaming Liu, Hao Chen, Pengju An +12
A fundamental objective of manipulation policy design is to endow robots to comprehend human instructions, reason about scene cues, and execute generalized actions in dynamic envir…