Call for Papers
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:
- Humans vs. machines: A comparative study of human-level mathematical reasoning and current AI techniques. How do they differ, complement one another, or intersect?
- Measuring mathematical reasoning: How do we design benchmarks which accurately evaluate mathematical reasoning abilities, especially in an era of large language models?
- New capabilities: How do we move beyond our current techniques?
- Education: What role can deep learning models play in mathematics education, especially in contexts with limited educational resources?
- Applications: What applications could AI systems enable in the near- and long-term? Example domains include software verification, sciences, engineering, finance, education, and mathematics itself.
Important Dates
Paper submission opens: Aug 1, 2023
Deadline for paper submission: September 29, 2023 (Extended to Oct 02, 2023)
Notification: October 27, 2023
Camera Ready: November 15, 2023
Workshop: December 15, 2023
Submission Requirements
Submissions to MATH-AI 2023 are limited to 4 pages of content, but may contain an unlimited number of pages for references and appendices. The latter may not necessarily be read by the reviewers. We request and recommend that authors rely on the supplementary material only to include minor details (e.g., hyperparameter settings, reproducibility information, etc.) that do not fit in the 4 pages. The review process is double-blind, so please ensure that all papers are appropriately anonymised.
All submissions must be formatted with LaTeX using the NeurIPS paper format (Adapted).
All accepted papers will be presented in an in-person poster session, and some will be selected for oral presentation. We also permit papers that have been recently published or are under submission to another venue. Please mark such papers accordingly upon submission. The page limit for these submissions is 4 pages. Accepted papers will be displayed on the MATH-AI 2023 homepage, but are to be considered non-archival.
Submission Link: https://openreview.net/group?id=NeurIPS.cc/2023/Workshop/MATH-AI
Camera-ready Requirements
The final version of all accepted papers will be given one additional page of content (up to 5 pages) so that reviewers’ comments can be taken into account.
Please email any enquiries to mathai.neurips2023@gmail.com.