collaborators

8 papers

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

iMaC: Translating Actions into Motion and Contact Images for Embodied World Models

Zhenyu Wu, Xiuwei Xu, Yukun Zhou +8

Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventional embodied frameworks rely o…

cs.RO2026

ViVa: A Video-Generative Value Model for Robot Reinforcement Learning

Jindi Lv, Hao Li, Jie Li +11

Vision-language-action (VLA) models have advanced robot manipulation through large-scale pretraining, but real-world deployment remains challenging due to partial observability and…

cs.CV2026

GigaWorld-Policy: An Efficient Action-Centered World--Action Model

Angen Ye, Boyuan Wang, Chaojun Ni +21

World-Action Models (WAM) initialized from pre-trained video generation backbones have demonstrated remarkable potential for robot policy learning. However, existing approaches fac…

cs.CV2026

GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning

GigaBrain Team, Boyuan Wang, Bohan Li +23

Vision-language-action (VLA) models that directly predict multi-step action chunks from current observations face inherent limitations due to constrained scene understanding and we…

cs.CV2025

GigaWorld-0: World Models as Data Engine to Empower Embodied AI

GigaWorld Team, Angen Ye, Boyuan Wang +22

World models are emerging as a foundational paradigm for scalable, data-efficient embodied AI. In this work, we present GigaWorld-0, a unified world model framework designed explic…

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…