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cs.RO2026

LoopWAM: Closed-Loop Generalist Policy Improvement from Deployment Rollouts

Wenxuan Guo, Yingping Liang, Zhaoguo Wang +11

Scaling expert demonstrations alone does not enable generalist robot policies to improve from deployment. Real-world rollouts contain successes, suboptimal behavior, and failures:…

cs.RO2026

SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation

Changyuan Wang, Chubin Zhang, Zhenyu Wu +8

Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on robotic manipulation benchmarks. How…

cs.RO2026

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

GigaWorld Team, Angen Ye, Angyuan Ma +26

World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as dense supervision for physicall…

cs.RO2026

GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

GigaWorld Team, Angyuan Ma, Boyuan Wang +24

Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, robotic policies require slow,…

cs.RO2026

R2RDreamer: 3D-aware Data Augmentation for Spatially-generalized 2D Manipulation Policies

Xiuwei Xu, Haowen Sun, Angyuan Ma +7

Spatial generalization is critical for imitation-learned manipulation policies, but achieving it typically requires scaling demonstrations across diverse object poses, robot config…

cs.RO2026

ShapeGen: Robotic Data Generation for Category-Level Manipulation

Yirui Wang, Xiuwei Xu, Angyuan Ma +3

Manipulation policies deployed in uncontrolled real-world scenarios are faced with great in-category geometric diversity of everyday objects. In order to function robustly under su…

cs.RO2026

F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation

Haoyu Wei, Xiuwei Xu, Ziyang Cheng +5

Asynchronous inference has emerged as a prevalent paradigm in robotic manipulation, achieving significant progress in ensuring trajectory smoothness and efficiency. However, a syst…