# Call for Papers

The goal of this workshop is to find out “when machines can surpass human experts in different mathematical domains?”. To investigate this question, we are interested in bringing together a group of scholars from various backgrounds, institutions, and disciplines to discuss areas related to the following:

**Humans vs. machines**: How does human-level mathematical reasoning differ from today’s methods?**Measurement**: How should we measure and benchmark progress moving forward?**Key technical areas**: What machine learning advances are needed to close the gap with humans?**Beyond human-level**: Is human-level reasoning the right goal for all aspects of mathematics?**Augmentations**: How can we develop methods that can augment humans in performing mathematical reasoning tasks (e.g. teaching, formulating conjectures, identifying interesting theorems to prove)?

The intended outcome is to identify missing elements and meaningful directions for future research related to mathematical reasoning. To this end, we welcome papers on areas related, but not limited, to:

**Problem solving**: informal and symbolic problem solving tasks and associated methods (e.g. word and geometry problems, IQ tests, symbolic regression).**Theorem proving**: machine learning methods for automated and interactive theorem proving and related problems (e.g. conjecturing, autoformalization).**Reasoning in related areas**: program synthesis and software verification, common-sense andnatural language reasoning, retrosynthesis analysis, cognitive and neurosymbolic reasoning mechanisms.

In addition to the problem areas above, we are interested in research related to the following themes:

**Algorithms**: Can better algorithms (e.g. learning, planning) close the gap with human-level abilities?**Analysis**: What are the drawbacks or limitations of current models and evaluation methods with respect to mathematical reasoning (e.g. robustness, generalization)?**Flexibility**: How do we build mathematical reasoning systems that are generic and flexible?**Reliability**: How can we ensure that models generate reliable and trustworthy results?**Transfer**: Can we leverage common structure between tasks to improve general mathematical ability?

### Important Dates

**Paper submission opens:** July 18, 2022 (12:00am Pacific Time)

**Deadline for paper submission**: September 30, 2022 (11:59pm Pacific Time)

**Notification:** October 20, 2022 (11:59pm Pacific Time)

**Camera Ready:** November 03, 2022 (11:59pm Pacific Time)

**Workshop:** December 03, 2022

### Submission Requirements

Submissions to MATH-AI 2022 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 published on the MATH-AI 2022 homepage, but are to be considered non-archival.

Submission Link: https://cmt3.research.microsoft.com/MATHAI2022

Please email any enquiries to mathai.neurips2022@gmail.com.