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From the 1 of 16 linked papers with an AI index.

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20242026
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cs.RO2026

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

GigaWorld Team, Angen Ye, Angyuan Ma +26

The paper introduces GigaWorld-Policy-0.5, a robot control model that learns from future visual dynamics during training but generates actions only at inference, achieving faster (…

cs.RO2026

HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models

Angen Ye, Weijie Ke, Xiaofeng Wang +7

World-action (WA) models can generate long-horizon action chunks for general-purpose robotic manipulation, but they remain vulnerable to calibration, perception, and contact-dynami…

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

EgoDemoGen: Egocentric Demonstration Generation for Viewpoint Generalization in Robotic Manipulation

Yuan Xu, Jiabing Yang, Xiaofeng Wang +16

Imitation learning based visuomotor policies have achieved strong performance in robotic manipulation, yet they often remain sensitive to egocentric viewpoint shifts. Unlike third-…

cs.RO2025

GigaBrain-0: A World Model-Powered Vision-Language-Action Model

GigaBrain Team, Angen Ye, Boyuan Wang +24

Training Vision-Language-Action (VLA) models for generalist robots typically requires large-scale real-world robot data, which is expensive and time-consuming to collect. The ineff…

cs.RO2025

MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

Haoyun Li, Ivan Zhang, Runqi Ouyang +12

Vision Language Action (VLA) models derive their generalization capability from diverse training data, yet collecting embodied robot interaction data remains prohibitively expensiv…