Yanyuan Qiao
Papers
2
Total Citations
28
H-Index
2
About
Yanyuan Qiao is an emerging researcher specializing in Vision-and-Language Navigation (VLN) and embodied AI, with a focus on bridging natural language understanding and intelligent agent navigation. Their most notable contribution, "March in Chat: Interactive Prompting for Remote Embodied Referring Expression" (2023), addresses one of the field's more demanding challenges: enabling autonomous agents to navigate complex environments using only high-level, human-like instructions rather than granular step-by-step directives. This work tackles the REVERIE benchmark, a particularly challenging VLN task that spans both indoor and outdoor settings and requires agents to interpret abstract commands in a manner closely resembling real-world human communication. By introducing an interactive prompting framework, Qiao and collaborators advanced the state of the art in making navigation agents more responsive and contextually aware, contributing meaningfully to the broader goal of deployable, instruction-following robots. The paper has accumulated 28 citations across indexed sources, reflecting growing interest from the embodied AI and multimodal learning communities. Qiao's research sits at an exciting intersection of computer vision, natural language processing, and robotics — areas poised to define the next generation of human-machine interaction.
Research Focus
Key Achievements
Top Papers
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- 2