Zijiao Yang

Zijiao Yang (杨子蛟 in Chinese) is a Ph.D. student at Oregon State University, advised by Prof. Stefan Lee. He earned Master’s degree in computer science at University of Colorado at Boulder.

His research interest is ultimately driven by the mystery of human intelligence, and he believes achieving a “deep” level of language grounding is one of the key steps. He has worked on semantic role labeling during Master’s. Currently, he takes vision-language navigation tasks as a platform to study groundness of natural language onto vision and actions.

News

Feb 27, 2023	Our work: “Behavioral Analysis of Vision-and-Language Navigation Agents” has been accepted to CVPR 2023 (25%)
May 11, 2021	Created personal website!

Selected publications

CVPR

Behavioral Analysis of Vision-and-Language Navigation Agents

Yang, Zijiao, Majumdar, Arjun, and Lee, Stefan

Computer Vision and Pattern Recognition 2023

Abs HTML

To be successful, Vision-and-Language Navigation (VLN) agents must be able to ground instructions to actions based on their surroundings. In this work, we develop a methodology to study agent behavior on a skill-specific basis – examining how well existing agents ground instructions about stopping, turning, and moving towards specified objects or rooms. Our approach is based on generating skill-specific interventions and measuring changes in agent predictions. We present a detailed case study analyzing the behavior of a recent agent and then compare multiple agents in terms of skill-specific competency scores. This analysis suggests that biases from training have lasting effects on agent behavior and existing models have grounding simple referring expressions. Our comparisons between models shows that skill-specific scores correlate with improvements in overall VLN task performance.