Jinhua Xiao

Papers

1

Total Citations

3

H-Index

1

About

Jinhua Xiao is an emerging researcher working at the intersection of artificial intelligence and robotics, with a particular focus on human-robot collaboration enhanced by large language models (LLMs). Their work explores how cutting-edge natural language processing technologies can be meaningfully integrated into robotic systems to improve human-machine interaction, accessibility, and collaborative task performance. Xiao's most notable contribution to date is a systematic review examining the role of large language models in human-robot collaboration, published in 2026. This comprehensive survey maps current trends, identifies methodological approaches, and critically outlines the challenges researchers face when deploying LLMs in real-world robotic contexts — work that has already garnered early citations, signaling growing interest within the community. By synthesizing a rapidly evolving field into a structured, accessible framework, Xiao's research serves as a valuable resource for both newcomers and established researchers navigating the complex landscape of AI-driven robotics. As LLM-powered robotic systems become increasingly prevalent across industries, Xiao's systematic scholarship positions them as a thoughtful voice shaping how the field understands and addresses its most pressing technical and ethical challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Large language models in human-robot collaboration: A systematic review, trends, and challenges
3 citations · 2026
📈 Most Prolific Year: 2026 (1 Papers)
🤝 Key Collaborators: 2

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago