ACL2023
LaTeX2Solver: a Hierarchical Semantic Parsing of LaTeX Document into Code for an Assistive Optimization Modeling Application
Rindra Ramamonjison, Timothy T. L. Yu, Linzi Xing, Mahdi Mostajabdaveh, Xiaorui Li, Xiaojin Fu, Xiongwei Han, Yuanzhe Chen, Ren Li, Kun Mao, Yong Zhang
2 citations
Abstract
We demonstrate an interactive system to help operations research (OR) practitioners convert the mathematical formulation of optimization problems from LaTeX document format into the solver modeling language. In practice, a manual translation is cumbersome and timeconsuming. Moreover, it requires an in-depth understanding of the problem description and a technical expertise to produce the modeling code. Thus, our proposed system LATEX-SOLVER helps partially automate this conversion and help the users build optimization models more efficiently. In this paper, we describe its interface and the components of the hierarchical parsing system. A video demo walkthrough is available online. 1