Recent advances in LLMs for Mathematics

_{JOINT PACM /CSML COLLOQUIUM}

Abstract:

I will review the progress of large language models for mathematics over the last 3 years, from barely solving high school level mathematics to solving some minor open problems in convex optimization, combinatorics and probability theory. The emphasis will be on trying to identify the shape of the current frontier capabilities, as it stands today, finding out both where it's helpful and where it's still falling short as a research assistant.

Sebastien Bubeck - Bio

Sebastien Bubeck is currently a research lead at OpenAI. Previously he served as VP AI and Distinguished Scientist at Microsoft, spending 10 years in Microsoft Research, and before that he was an assistant professor at Princeton University. His work on machine learning, convex optimization and online algorithms won several best paper awards, and more recently his work on Large (and Small) Language Models, including their applications to science, were featured in mainstream media such as the New York Times and Wired.