GOLD: Geometry Problem Solver with Natural Language Description

This paper presents our contribution towards the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024) with the title “GOLD: Geometry Problem Solver with Natural Language Description”.
To know more about the “NAACL 2024” please visit “2024.naacl.org”
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Addressing the challenge of automated geometry math problem-solving in artificial intelligence (AI) involves understanding multi-modal information and mathematics. Current methods struggle with accurately interpreting geometry diagrams, which hinders effective problem-solving. To tackle this issue, we present the Geometry problem sOlver with natural Language Description (GOLD) model. GOLD enhances the extraction of geometric relations by separately processing symbols and geometric primitives within the diagram. Subsequently, it converts the extracted relations into natural language descriptions, efficiently utilizing large language models to solve geometry math problems. Experiments show that the GOLD model outperforms the Geoformer model, the previous best method on the UniGeo dataset, by achieving accuracy improvements of 12.7% and 42.1% in calculation and proving subsets. Additionally, it surpasses the former best model on the PGPS9K and Geometry3K datasets, PGPSNet, by obtaining accuracy enhancements of 1.8% and 3.2%, respectively
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This work was conducted in NeuraSearch Laboratory by Jiaxin Zhang and Dr Yashar Moshfeghi.
To know more about Jiaxin Zhang please visit knightzhang625....
To know more about Dr Yashar Moshfeghi, please visit academic.yashmo... or / yashar-moshfeghi .
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Thank you.

[@ClaudiaCarranza1]

This is interesting, and I am curious about the application of this software as an instructional tool in the Geometry classroom...