15 citations · 29 across the 13 of their papers we have counts for
15 papers
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:…
GigaBrain-WBC-0.5: A Behavior World Model for Robust Humanoid Whole-Body Tracking with Environment Interaction
Ziyang Cheng, Tianshu Tang, Jinxin Lan +19
General-purpose motion trackers enable humanoid robots to follow diverse whole-body motions while maintaining balance, but are trained only on flat ground, failing to exploit biped…
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…
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,…
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…
OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs
Yifei Li, Pengyiang Liu, Yuhang Zang +4
Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous egocentric streams, often using evidence outside the current view. Ex…
Syll: Open-Source Personal Automation with Cross-Surface Execution
Bo Zhang, Borui Zhang, Chenghao Jiang +5
Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface and offer limited support for…
Vega: Learning to Drive with Natural Language Instructions
Sicheng Zuo, Yuxuan Li, Wenzhao Zheng +3
Vision-language-action models have reshaped autonomous driving to incorporate languages into the decision-making process. However, most existing pipelines only utilize the language…
Geometry-Aware Single-Image 4D Synthesis via Dense Trajectory Generation
Yanran Zhang, Ziyi Wang, Wenzhao Zheng +3
Generating interactive and dynamic 4D scenes from a single static image remains a core challenge. Most existing generate-then-reconstruct and reconstruct-then-generate methods deco…
DriveGen3D: Boosting Feed-Forward Driving Scene Generation with Efficient Video Diffusion
Weijie Wang, Jiagang Zhu, Zeyu Zhang +14
We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies…
R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation
Xiuwei Xu, Angyuan Ma, Hankun Li +4
Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to work robustly under different spatial dis…
Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…
WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens
Xiaofeng Wang, Zheng Zhu, Guan Huang +3
World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation. However, existing world models are confined to…
DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
Xiaofeng Wang, Zheng Zhu, Guan Huang +3
World models, especially in autonomous driving, are trending and drawing extensive attention due to their capacity for comprehending driving environments. The established world mod…
Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline
Xianda Guo, Zheng Zhu, Tian Yang +6
Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognit…