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Xianyuan Zhan

Institute for AI Industry Research

48 papers hereh-index 212k citations55 works total

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

author position
  • first author1
  • middle author21
  • last author24

Across the 46 of 48 papers where every author was matched, so the position is known.

fields
  • cs.LG25
  • cs.RO16
  • cs.AI3
  • cs.CV3
  • cs.CL1
affiliations
  • Institute for AI Industry Research
Homepage
same name
  • Xianyuan Zhan — 8 papers, h 21
  • Xianyuan Zhan — 4 papers, h 3
  • Xianyuan Zhan — 1 paper, h 2

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
20212026
most citedOpenChat: Advancing Open-source Language Models with Mixed-Quality Data

27 citations · 86 across the 44 of their papers we have counts for

collaborators
Showing 2024 · cs.ROShow all

4 papers · 2 filters

cs.RO2024

Robo-MUTUAL: Robotic Multimodal Task Specification via Unimodal Learning

Jianxiong Li, Zhihao Wang, Jinliang Zheng +8

Multimodal task specification is essential for enhanced robotic performance, where \textit{Cross-modality Alignment} enables the robot to holistically understand complex task instr…

cs.RO2024

xTED: Cross-Domain Adaptation via Diffusion-Based Trajectory Editing

Haoyi Niu, Qimao Chen, Tenglong Liu +5

Reusing pre-collected data from different domains is an appealing solution for decision-making tasks, especially when data in the target domain are limited. Existing cross-domain p…

cs.RO2024

DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning

Jianxiong Li, Jinliang Zheng, Yinan Zheng +9

Multimodal pretraining is an effective strategy for the trinity of goals of representation learning in autonomous robots: 1) extracting both local and global task progressions; 2)…

cs.RO2024

A Comprehensive Survey of Cross-Domain Policy Transfer for Embodied Agents

Haoyi Niu, Jianming Hu, Guyue Zhou +1

The burgeoning fields of robot learning and embodied AI have triggered an increasing demand for large quantities of data. However, collecting sufficient unbiased data from the targ…

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