4 papers · 1 filter
DepState-JEPA: Learning Depth-Grounded State Representation for Visual Perception and Manipulation
Xiujian Liang, Liuyuan Na, Zehao Du +6
Predictive representations for robot manipulation should connect scene geometry with the state changes induced by actions. Our intuition is that understanding what an action will c…
Explicit Kinematic Guidance from Analytic Concepts for Vision-Language-Action Models
Mingyang Sun, Jiude Wei, Xiujian Liang +4
Current Vision-Language-Action (VLA) models rely mainly on 2D inputs, neglecting the rich object structural information and commonsense knowledge inherent in the 3D physical world.…
Analytic Concept-Centric Memory for Agentic Embodied Manipulation
Mingyang Sun, Xiujian Liang, Jiude Wei +4
Long-horizon embodied manipulation requires agents to remember persistent objects, track changing scene states, and reuse prior interaction knowledge. However, existing agent memor…
OptArgus: A Multi-Agent System to Detect Hallucinations in LLM-based Optimization Modeling
Zhong Li, Zihan Guo, Xiaohan Lu +5
Large language models (LLMs) are increasingly used to translate natural-language optimization problems into mathematical formulations and solver code, but matching the reference ob…