7 papers
The Curse of Precision: A Data Scaling Law for High-Precision Robotic Manipulation
Cuijie Xu, Yuanfan Xu, Min Xue +5
While scaling laws for imitation learning have primarily focused on generalization in open-world settings, the relationship between data and precision in closed-world tasks like ro…
Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos
Runze Xu, Yiluo Zhang, Jian Wang +2
Training generalist Vision-Language-Action(VLA) models typically requires massive, diverse robotic datasets with high-fidelity action annotations. While egocentric human manipulati…
ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation
Yu Sun, Meng Cao, Yang Ping +24
Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their empirical progress remains constra…
STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning
Zhihao Liu, Qiuyi Gu, Yitao Wang +16
Real-world robot learning increasingly relies on heterogeneous data, but demonstrations and rollouts often mix useful progress with stalls, corrections, and suboptimal behavior. Ef…
COMPASS: Confined-space Manipulation Planning with Active Sensing Strategy
Qixuan Li, Chen Le, Dongyue Huang +2
Manipulation in confined and cluttered environments remains a significant challenge due to partial observability and complex configuration spaces. Effective manipulation in such en…
HCLM: A Hierarchical Framework for Cooperative Loco-Manipulation with Dual Quadrupeds
Qixuan Li, Chen Le, Jincheng Yu +1
We introduce HCLM, a hierarchical framework for general-purpose cooperative loco-manipulation with dual quadrupedal systems. Coordinating multi-robot collaborative manipulation acr…