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Minghuan Liu

24 papers hereh-index 131.1k citations32 works total

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

author position
  • first author7
  • middle author15

Across the 22 of 24 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.RO8
  • cs.AI7
  • cs.MA1
same name
  • Minghuan Liu — 6 papers, h 4
  • Minghuan Liu — 3 papers, h 4
  • Minghuan Liu — 1 paper

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
20202026
most citedVision-Language Foundation Models as Effective Robot Imitators

19 citations · 85 across the 24 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.RO2024

D4W: Dependable Data-Driven Dynamics for Wheeled Robots

Yunfeng Lin, Minghuan Liu, Yong Yu

Wheeled robots have gained significant attention due to their wide range of applications in manufacturing, logistics, and service industries. However, due to the difficulty of buil…

cs.RO2024★ 2 cited

GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs

Pu Hua, Minghuan Liu, Annabella Macaluso +4

Robotic simulation today remains challenging to scale up due to the human efforts required to create diverse simulation tasks and scenes. Simulation-trained policies also face scal…

cs.LG2024

DyDiff: Long-Horizon Rollout via Dynamics Diffusion for Offline Reinforcement Learning

Hanye Zhao, Xiaoshen Han, Zhengbang Zhu +4

With the great success of diffusion models (DMs) in generating realistic synthetic vision data, many researchers have investigated their potential in decision-making and control. M…

cs.AI2024

Looking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem

Jingxiao Chen, Ziqin Gong, Minghuan Liu +3

Many real-world problems can be formulated as a constrained Traveling Salesman Problem (TSP). However, the constraints are always complex and numerous, making the TSPs challenging…

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