# Zulip Chat Archive

## Stream: Machine Learning for Theorem Proving

### Topic: Paper: A Survey of Deep Learning for Mathematical Reasoning

#### Tom Chen (Jan 03 2023 at 00:01):

Just come across this (review) paper :) Given that there seems to be tradition to share papers in this channel, I just link it here:

https://arxiv.org/abs/2212.10535

A Survey of Deep Learning for Mathematical Reasoning

Pan Lu, Liang Qiu, Wenhao Yu, Sean Welleck, Kai-Wei Chang

Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in various fields, including science, engineering, finance, and everyday life. The development of artificial intelligence (AI) systems capable of solving math problems and proving theorems has garnered significant interest in the fields of machine learning and natural language processing. For example, mathematics serves as a testbed for aspects of reasoning that are challenging for powerful deep learning models, driving new algorithmic and modeling advances. On the other hand, recent advances in large-scale neural language models have opened up new benchmarks and opportunities to use deep learning for mathematical reasoning. In this survey paper, we review the key tasks, datasets, and methods at the intersection of mathematical reasoning and deep learning over the past decade. We also evaluate existing benchmarks and methods, and discuss future research directions in this domain.

Last updated: Dec 20 2023 at 11:08 UTC