Extracting the Unknown from Long Math Problems
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Abstract (arXiv)
In problem solving, understanding the problem that one seeks to solve is an essential initial step. In this paper, we propose computational methods for facilitating problem understanding through the task of recognizing the unknown in specifications of long Math problems. We focus on the topic of Probability. Our experimental results show that learning models yield strong results on the task, a promising first step towards human interpretable, modular approaches to understanding long Math problems.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 22 Mar 2021.
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References · 13
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