Delves into training and applications of Vision-Language-Action models, emphasizing large language models' role in robotic control and the transfer of web knowledge. Results from experiments and future research directions are highlighted.
Explores analog network coding for wireless imaging in challenging conditions, showcasing its potential in human pose reconstruction and self-driving cars.
Explores advancements in robot learning for autonomy at scale, covering deep learning challenges, efficient architecture, benchmarking results, and societal implications.
Covers the principles of Scanning Electron Microscopy, including SEM signals, detectors, and energy spectrum of electrons, as well as the efficiency of X-ray generation.
Explores bug-finding, verification, and the use of learning-aided approaches in program reasoning, showcasing examples like the Heartbleed bug and differential Bayesian reasoning.
