Do Joint Audio-Video Generation Models Understand Physics?
The paper introduces AV-Phys Bench, a benchmark for physical commonsense in joint audio-video generation.
I'm a Master's student in Technology Innovation (Robotics Track) at the University of Washington (GPA: 3.83/4.0), with a B.S. in Software Engineering from Tongji University, and I completed exchange coursework at UC Berkeley. My work spans robotics, embedded systems, and full-stack software development. My research interests include robot learning, reinforcement and imitation learning, world models, safety verification, human-robot interaction, brain-machine interfaces and neural decoding.
M.S. in Technology Innovation (Robotics Track), GPA 3.83/4
Courses: Managing Data and Signal Processing, Robotic Sensing and Mobility, Neuroscience (NEUSCI 401)
B.S. in Software Engineering, GPA 88.25/100
Courses: Linear Algebra, Probability and Mathematical Statistics, Statistics Analysis and Modeling, Data Structures, Computer Graphics
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Languages: C++, Python | ML: PyTorch, scikit-learn, world models, RL and imitation learning | Robotics: ROS2, LeRobot, Isaac Lab, NVIDIA Jetson | Tools: Docker, Git
Also: Java, C#, JavaScript, CUDA, MoveIt, Fusion 360
The paper introduces AV-Phys Bench, a benchmark for physical commonsense in joint audio-video generation.
Chenming Ge, Fan Zhang