@inproceedings{ramamonjison-etal-2023-latex2solver,
    title = "{L}a{T}e{X}2{S}olver: a Hierarchical Semantic Parsing of {L}a{T}e{X} Document into Code for an Assistive Optimization Modeling Application",
    author = "Ramamonjison, Rindra  and
      Yu, Timothy  and
      Xing, Linzi  and
      Mostajabdaveh, Mahdi  and
      Li, Xiaorui  and
      Fu, Xiaojin  and
      Han, Xiongwei  and
      Chen, Yuanzhe  and
      Li, Ren  and
      Mao, Kun  and
      Zhang, Yong",
    editor = "Bollegala, Danushka  and
      Huang, Ruihong  and
      Ritter, Alan",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-demo.45",
    doi = "10.18653/v1/2023.acl-demo.45",
    pages = "471--478",
    abstract = "We demonstrate an interactive system to help operations research (OR) practitioners convert the mathematical formulation of optimization problems from TeX document format into the solver modeling language. In practice, a manual translation is cumbersome and time-consuming. Moreover, it requires an in-depth understanding of the problem description and a technical expertise to produce the modeling code. Thus, our proposed system TeX2Solver 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 walk-through is available online at \url{http://bit.ly/3kuOm3x}",
}

We demonstrate an interactive system to help operations research (OR) practitioners convert the mathematical formulation of optimization problems from TeX document format into the solver modeling language. In practice, a manual translation is cumbersome and time-consuming. Moreover, it requires an in-depth understanding of the problem description and a technical expertise to produce the modeling code. Thus, our proposed system TeX2Solver 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 walk-through is available online at \url{http://bit.ly/3kuOm3x}
Ramamonjison, Rindra Yu, Timothy Xing, Linzi Mostajabdaveh, Mahdi Li, Xiaorui Fu, Xiaojin Han, Xiongwei Chen, Yuanzhe Li, Ren Mao, Kun Zhang, Yong
LaTeX2Solver: a Hierarchical Semantic Parsing of LaTeX Document into Code for an Assistive Optimization Modeling Application