27 citations · 48 across the 14 of their papers we have counts for
9 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…
ObjDream: Guiding Vision-Language-Action Models with Object-Level Understanding and Future State Prediction
Huailiang Ma, Yuxuan Li, Ziyi Zhao +7
Vision-language-action (VLA) models have emerged as a powerful paradigm for robotic manipulation, enabling robots to generate actions from visual observations and language instruct…
PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control
Lei Ye, Haibo Gao, Yitang Li +10
Diffusion models provide a flexible framework for motion generation, but turning this flexibility into closed-loop humanoid control remains challenging. Hierarchical generator-trac…
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…
RealDiff: Bridging Real-World Gap in Robot Manipulation via Depth Diffusion
Xiujian Liang, Jiacheng Liu, Mingyang Sun +3
Robot manipulation in the real world is fundamentally constrained by the visual sim2real gap, where depth observations collected in simulation fail to reflect the complex noise pat…
Executable Analytic Concepts as the Missing Link Between VLM Insight and Precise Manipulation
Mingyang Sun, Jiude Wei, Qichen He +3
Enabling robots to perform precise and generalized manipulation in unstructured environments remains a fundamental challenge in embodied AI. While Vision-Language Models (VLMs) hav…
Physically Ground Commonsense Knowledge for Articulated Object Manipulation with Analytic Concepts
Jiude Wei, Yuxuan Li, Cewu Lu +1
We humans rely on a wide range of commonsense knowledge to interact with an extensive number and categories of objects in the physical world. Likewise, such commonsense knowledge i…
Discovering Conceptual Knowledge with Analytic Ontology Templates for Articulated Objects
Jianhua Sun, Yuxuan Li, Longfei Xu +3
Human cognition can leverage fundamental conceptual knowledge, like geometric and kinematic ones, to appropriately perceive, comprehend and interact with novel objects. Motivated b…