Yue Weng
Papers
1
Total Citations
22
H-Index
1
About
Yue Weng is a leading researcher in embodied AI and human-robot interaction, with a focus on vision-dialog navigation (VDN) and autonomous communication agents. His most cited work, "Self-Motivated Communication Agent for Real-World Vision-Dialog Navigation" (2021, 22 citations), addresses a critical limitation in conventional VDN systems: the inability of agents to ask questions dynamically during navigation. By introducing a self-motivated framework that allows agents to initiate dialogue at any point, Weng’s research eliminates the need for expensive, pre-annotated dialogue data and enhances real-world applicability. This contribution has significant implications for assistive robotics and autonomous systems, enabling more natural and efficient human-robot collaboration. Weng’s work bridges the gap between static, scripted interactions and fluid, context-aware communication, paving the way for agents that can actively seek information to complete complex tasks. His research is widely recognized for its practical impact, advancing the frontier of intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1Self-Motivated Communication Agent for Real-World Vision-Dialog Navigation22 citations · 2021