(West Meeting Room 118-120, Vancouver, December 14, 2024, Website)

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Overview

Mathematical reasoning is a fundamental aspect of human cognition that has been studied by scholars ranging from philosophers to cognitive scientists and neuroscientists. Mathematical reasoning involves analyzing complex information, identifying patterns and relationships, and drawing logical conclusions from evidence. It is central to many applications in science, engineering, finance, and everyday contexts.

Recent advancements in large language models (LLMs) have unlocked new opportunities at the intersection of artificial intelligence and mathematical reasoning, ranging from new methods that solve complex problems or prove theorems, to new forms of human-machine collaboration in mathematics and beyond.

Our proposed workshop is centered on the intersection of deep learning and mathematical reasoning, with an emphasis on, but not limited to, large language models. Our guiding theme is:

“To what extent can machine learning models comprehend mathematics, and what applications could arise from this capability?”

To address this question, we aim to bring together a diverse group of scholars from different backgrounds, institutions, and disciplines into our workshop. Our objective is to foster a lively and constructive dialogue on areas related, but not limited, to the following:


Speakers & Panelists

Samy Bengio
Samy Bengio
Apple
Noam Brown
Noam Brown
OpenAI
Dawn Song
Dawn Song
UC Berkeley
Adam Wagner
Adam Wagner
Google DeepMind
James Zou
James Zou
Stanford University
More Info

Organizers

Alex Gu
Alex Gu
MIT
Gabriel Poesia
Gabriel Poesia
Stanford
Hattie Zhou
Hattie Zhou
Anthropic
Pan Lu
Pan Lu
Stanford
Swaroop Mishra
Swaroop Mishra
Google DeepMind
Kai-Wei Chang
Kai-Wei Chang
UCLA, Alexa AI

Related Venues


Contact: mathai.neurips2024@gmail.com.