5 papers · 1 filter
E0.5: From Reconstructive to Future-Predictive 3D Foundations for Robotic World-Action Modeling
Era AI Lab Team, Jianhao Lai, Zhihao Zhan +24
World-action models (WAMs) offer a promising framework for embodied intelligence, yet mainstream approaches remain centered on video foundation models or vision-language models. Ev…
AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots
Likui Zhang, Tao Tang, Zhihao Zhan +9
Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robotic tasks often involve long-horizon,…
RADAR: Benchmarking Vision-Language-Action Generalization via Real-World Dynamics, Spatial-Physical Intelligence, and Autonomous Evaluation
Yuhao Chen, Zhihao Zhan, Xiaoxin Lin +11
VLA models have achieved remarkable progress in embodied intelligence; however, their evaluation remains largely confined to simulations or highly constrained real-world settings.…
Stable Language Guidance for Vision-Language-Action Models
Zhihao Zhan, Yuhao Chen, Jiaying Zhou +5
Vision-Language-Action (VLA) models have demonstrated impressive capabilities in generalized robotic control; however, they remain notoriously brittle to linguistic perturbations.…
E0: Enhancing Generalization and Fine-Grained Control in VLA Models via Tweedie Discrete Diffusion
Zhihao Zhan, Jiaying Zhou, Likui Zhang +10
Vision-Language-Action (VLA) models offer a unified framework for robotic manipulation by integrating visual perception, language understanding, and control generation. However, ex…