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AutoMATES: Automated Model Assembly from Text, Equations, and Software

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arxiv 2001.07295 v1 pith:UFUEIQ73 submitted 2020-01-21 cs.AI cs.MMcs.SE

Adarsh Pyarelal , Marco A. Valenzuela-Escarcega , Rebecca Sharp , Paul D. Hein , Jon Stephens , Pratik Bhandari , HeuiChan Lim , Saumya Debray
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Clayton T. Morrison
This is my paper · ORCID
classification cs.AIcs.MMcs.SE
keywords modelsautomatescodecomplicateddifferentdomainsequationsrepresented
verification ladder T0 review T1 audit T2 compute T3 formal
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Models of complicated systems can be represented in different ways - in scientific papers, they are represented using natural language text as well as equations. But to be of real use, they must also be implemented as software, thus making code a third form of representing models. We introduce the AutoMATES project, which aims to build semantically-rich unified representations of models from scientific code and publications to facilitate the integration of computational models from different domains and allow for modeling large, complicated systems that span multiple domains and levels of abstraction.

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  1. Variable Extraction for Model Recovery in Scientific Literature

    cs.IR 2024-11 conditional novelty 6.0 of 10

    LLM-based variable extraction outperforms rule-based methods on a new 22-paper benchmark, with best F1 around 0.53 to 0.64, but all systems remain far from solved.

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