Deep Learning in Mathematical Reasoning: Recent Advances and Beyond
An tutorial at the 32nd International Joint Conference on Artificial Intelligence - IJCAI -23
Tutorial Abstract
This tutorial will provide an overview of the recent advances in deep learning for mathematical reasoning. It will cover various tasks and datasets, examine advancements in neural networks and pre-trained language models, and explore opportunities and challenges for future research.
Zhenwen Liang
Zhenwen is a PhD student at the University of Notre Dame, working on NLP for mathematical reasoning and large language models.
Pan Lu
Pan is a 4th-year PhD candidate in the Computer Science Department at UCLA, with a research goal to develop intelligent systems that can reason like humans and collaborate with them to accomplish complex tasks.
Sean Welleck
Sean Welleck is a Postdoctoral Scholar at the University of Washington and the Allen Institute for Artificial Intelligence, advised by Professor Yejin Choi. He is also an incoming assistant professor at CMU.
Ashwin Kalyan
Ashwin Kaylan is a research scientist at AI2, where he investigates the abilities and limitations of foundation models, especially in the context of hard reasoning problems.
Tutotial Schedule
Overview of Mathematical Reasoning
Fine-tuning-based Methods on Mathematical Reasoning
Deep Learning in Theorem Proving
Closing Remarks