Vision-language-action (VLA) and world-action (WAM) models map observations and instructions directly to robot actions. This directness ties a policy to training: minor layout or viewpoint changes cause failure, and instructions generalize poorly. The root cause lies in representation: task requirements, conditions, pr...
Hong-Cheng Gao, Jing-Jing Zhou, Ze Zheng et al.· 0 citations
Autonomous agents have made rapid progress in general-purpose computer use, but reliable automation of professional industrial engineering remains out of reach, as engineering workflows demand reasoning over geometric and physical constraints and dependencies preserved across software and design stages. We present Engi...
Hong-Cheng Gao, Hai-Long Qu, Yu-Ang Lei et al.· 0 citations
A one-round study provides initial evidence for PRD-guided self-evolution, motivating validation at larger scales and in industrial settings, and presents AgentOmnia, a framework coordinating task-space definition, data synthesis, post-training, evaluation, and improvement across To-Consumer (ToC), To-Business (ToB), a...
OmniaBench provides a broad and diagnostic benchmark for characterizing the capability boundaries of general agents across diverse scenarios with explicit state spaces, and introduces a ten-dimensional capability taxonomy and eight compositional atomic difficulty factors to support fine-grained evaluation and analysis.
