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YouTube

Unraveling Long Context: Existing Methods, Challenges, and Future Directions

Toronto Machine Learning Series (TMLS) via YouTube

Overview

Explore the technical challenges and potential solutions for scaling transformer models to handle longer context in this 32-minute Toronto Machine Learning Series talk presented by Cohere's Technical Staff Member Bowen Yang. Dive into current methodologies for extending context windows, examine the obstacles faced from both modeling and framework perspectives, and discover emerging directions for future development in the field of large language models.

Syllabus

Unraveling Long Context: Existing Methods, Challenges, and Future Directions

Taught by

Toronto Machine Learning Series (TMLS)

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