7 papers
Spark-0: Scaling Spatially Aligned Tactile Pretraining for Robot Dexterous Manipulation
Tianxing Chen, Wenwei Lin, Chuqiao Lyu +19
Generalist robot policies benefit from large-scale visual pretraining but often struggle with contact-rich dexterous manipulation, where force, compliance, and incipient slip are h…
AutoPruner: Agentic Depth Pruning for Vision-Language-Action Models
Tao Lin, Yikeng Chen, Qiwei Liang +3
Layer pruning reduces the size and inference cost of vision-language-action (VLA) models, but selecting a deployable configuration requires deciding both which layers to remove and…
DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation
Yan Qin, Yue Chen, Wenwei Lin +9
Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots and remain tied to embodiment…
Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels
Xinyu Yang, Tianxing Chen, Honghao Su +38
Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures can cause immediate physical…
RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
Tianxing Chen, Yue Chen, Zixuan Li +41
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…
A GPU-Parallel Framework for Heterogeneous Multi-Task Reinforcement Learning
Rui Zhang, Qiwei Wu, Zhengyu Zhang +7
GPU-parallel simulation provides abundant robot interaction, but existing benchmarks rarely combine this scale with heterogeneous manipulation tasks and standardized multi-task RL…
AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
Zixuan Jiang, Renjing Xu
Deciphering protein function remains a fundamental challenge in protein representation learning. The task presents significant difficulties for protein language models (PLMs) due t…