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Chao Tang

14 papers hereh-index 6122 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author8

Across the 12 of 14 papers where every author was matched, so the position is known.

fields
  • cs.RO14
same name
  • Chao Tang — 22 papers, h 17
  • Chao Tang — 8 papers, h 8
  • Chao Tang — 7 papers, h 24
  • Chao Tang — 6 papers, h 17
  • Chao Tang — 6 papers, h 22
  • Chao Tang — 5 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedDexterous Manipulation through Imitation Learning: A Survey

2 citations · 4 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.RO2025★ 2 cited

Dexterous Manipulation through Imitation Learning: A Survey

Shan An, Ziyu Meng, Chao Tang +9

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordi…

cs.RO2025

FlowPlan: Zero-Shot Task Planning with LLM Flow Engineering for Robotic Instruction Following

Zijun Lin, Chao Tang, Hanjing Ye +1

Robotic instruction following tasks require seamless integration of visual perception, task planning, target localization, and motion execution. However, existing task planning met…

cs.RO2025

HGDiffuser: Efficient Task-Oriented Grasp Generation via Human-Guided Grasp Diffusion Models

Dehao Huang, Wenlong Dong, Chao Tang +1

Task-oriented grasping (TOG) is essential for robots to perform manipulation tasks, requiring grasps that are both stable and compliant with task-specific constraints. Humans natur…

cs.RO2025

FUNCTO: Function-Centric One-Shot Imitation Learning for Tool Manipulation

Chao Tang, Anxing Xiao, Yuhong Deng +5

Learning tool use from a single human demonstration video offers a highly intuitive and efficient approach to robot teaching. While humans can effortlessly generalize a demonstrate…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.