5 papers · 1 filter
HOST:Robots Acquire Manipulation Skills in Seconds from a Single Human Video
Guangyan Chen, Meiling Wang, Te Cui +9
The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots. However, current methods still rely on a cumbersome training-…
ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation
Yu Sun, Meng Cao, Yang Ping +24
Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their empirical progress remains constra…
WALL-WM: Carving World Action Modeling at the Event Joints
Shalfun Li, Victor Yao, Charles Yang +28
WALL-WM is a World Action Model that shifts video-action learning from chunk-centric optimization to event-grounded Vision-Language-Action pretraining, using semantically coherent…
Wall-OSS-0.5 Technical Report
Ryan Yu, Pushi Zhang, Starrick Liu +24
Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs is almost invariably reporte…
Igniting VLMs toward the Embodied Space
Andy Zhai, Brae Liu, Bruno Fang +17
While foundation models show remarkable progress in language and vision, existing vision-language models (VLMs) still have limited spatial and embodiment understanding. Transferrin…