multimodal models

Efficient Long-Form Video Understanding: Scaling Perception, Selecting Evidence, and Adapting Computation

Shuming Liu, Ph.D. Student, Computer Science

Nov 18, 19:00 - 21:00

Zoom Meeting 95938664864

scene understanding Advanced Perception reasoning Efficient AI visual computing multimodal models

This dissertation advances efficient long-form video understanding by developing methods that allocate limited computational resources across three stages: scaling video perception, selecting relevant visual evidence, and adapting reasoning effort to individual questions.

KAUST-CEMSE-AMCS-PhD-Dissertation-Defense-Lijie-Hu-Towards-Usable-and-Useful-Explainable-A

Towards Usable and Useful Explainable AI

Lijie Hu, Ph.D. Student, Computer Science

Jul 7, 17:00 - 19:00

explainable AI Large Language Models multimodal models

This talk presents advancements in Explainable AI, spanning from classical deep learning to large language models, with contributions that enhance both the usability and usefulness of interpretability methods to improve trust, performance, and safety in AI systems.