6 papers
From Social Reasoning to Embodied Interaction: An Agentic Framework for Social Robots
Ziyu Cheng, Yuewen Guo, Zhirui Liu +5
Natural face-to-face human--robot interaction requires a robot to understand an evolving social situation, decide when to engage, and express its intent through coordinated physica…
EmbodiRSI: Recursive Self-Improvement for Data-Efficient Robot Adaptation
Haoran Lang, Haotao Lu, Shiyu Sang +6
Adapting robot manipulation policies to new tasks and environments remains highly data-intensive, while the data needed for further improvement depends on the policy's current capa…
SelfWAM: A Self-Grounded Unified World Action Model for Fast Robot Control
Bikang Pan, Fan Liu, Haotao Lu +2
World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future observations. However, conditioning future prediction only on the task prompt and ob…
ViTacWorld: Scaling Visuo-Tactile World Models for Contact-Rich Robot Manipulation
Yunao Huang, Shiyu Sang, Haotao Lu +6
Contact-rich robot manipulation requires physical interaction cues that are often invisible to cameras, making tactile sensing essential for robust control. However, scaling visuo-…
Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation
Zhaoyang Liu, Mokai Pan, Zhongyi Wang +5
Imitation learning with diffusion models has advanced robotic control by capturing the multi-modal action distributions. However, existing methods typically treat observations only…
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance
Wentao Jiang, Jingya Wang, Kaiyang Ji +3
Human action-reaction synthesis, a fundamental challenge in modeling causal human interactions, plays a critical role in applications ranging from virtual reality to social robotic…