activity
20232026
most citedHandDiffuse: Generative Controllers for Two-Hand Interactions via Diffusion Models

3 citations · 7 across the 29 of their papers we have counts for

collaborators
Showing 2026Show all

14 papers · 1 filter

cs.RO2026

Hand2Robot: Object-Centric 4D Hand Reconstruction from Human Demonstrations for Robotics

Zetao Du, Weiqing Wang, Hanbing Zhang +4

Human demonstrations can capture task-relevant manipulation without using the target robot, but the recorded hand motions cannot directly serve as robot action supervision. Hand re…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

LabEvolver: Training-Free Experience Evolution for Safe and Grounded Wet-Lab Agents

Jingya Wang, Yuyang Gao, Liuzhenghao Lv +2

We introduce LabEvolver, a training-free framework that equips safe and grounded wet-lab agents with episodic memory from execution experience. LabEvolver couples a state-grounded…

cs.RO2026

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-…

cs.HC2026

Super Star: Towards Streaming Real-time Interactive Agents for Digital Humans

Wentao Jiang, Youchen Xie, Haidi Fan +4

Existing co-speech gesture generation methods are predominantly studied in offline settings, where gestures are synthesized from complete speech segments. However, interactive digi…

cs.RO2026

TactiDex: A Real-World Tactile-Guided Benchmark for Human-Like Dexterous Manipulation

Suting Ni, Hanbing Zhang, Zhenyu Wei +4

Tactile feedback is fundamental to Hand-Object Interaction (HOI), governing contact formation, force regulation, and stable manipulation, making it essential for achieving true hum…

cs.CV2026

MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

Bin Li, Ruichi Zhang, Han Liang +4

Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage…

cs.CV2026

DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing

Kaiyang Ji, Bingsheng Qian, Binghuan Wu +3

We study real-time audio-responsive character control as a deployment-faithful problem: strictly causal, bounded-latency streaming that must generate coherent full-body motion at i…

cs.RO2026

PAPO-VLA: Planning-Aware Policy Optimization for Vision-Language-Action Models

Peizheng Guo, Jingyao Wang, Changwen Zheng +1

Vision-Language-Action (VLA) models show promising ability in language-guided robotic tasks. However, making VLA policies reliable remains challenging, because a manipulation task…

cs.GR2026

SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control

Jingyan Zhang, Han Liang, Ruichi Zhang +6

Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing methods remain constrained by a…

cs.AI2026

BioProAgent: Neuro-Symbolic Grounding for Constrained Scientific Planning

Yuyang Liu, Jingya Wang, Liuzhenghao Lv +1

Large language models (LLMs) have demonstrated significant reasoning capabilities in scientific discovery but struggle to bridge the gap to physical execution in wet-labs. In these…

cs.RO2026

UniHM: Unified Dexterous Hand Manipulation with Vision Language Model

Zhenhao Zhang, Jiaxin Liu, Ye Shi +1

Planning physically feasible dexterous hand manipulation is a central challenge in robotic manipulation and Embodied AI. Prior work typically relies on object-centric cues or preci…