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        <title>Learning Mathematical Properties of Integers</title>
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        <namePart type="given">Maria</namePart>
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            <namePart type="given">Jasmijn</namePart>
            <namePart type="family">Bastings</namePart>
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        <name type="personal">
            <namePart type="given">Yonatan</namePart>
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    <abstract>Embedding words in high-dimensional vector spaces has proven valuable in many natural language applications. In this work, we investigate whether similarly-trained embeddings of integers can capture concepts that are useful for mathematical applications. We probe the integer embeddings for mathematical knowledge, apply them to a set of numerical reasoning tasks, and show that by learning the representations from mathematical sequence data, we can substantially improve over number embeddings learned from English text corpora.</abstract>
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    <identifier type="doi">10.18653/v1/2021.blackboxnlp-1.30</identifier>
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%0 Conference Proceedings
%T Learning Mathematical Properties of Integers
%A Ryskina, Maria
%A Knight, Kevin
%Y Bastings, Jasmijn
%Y Belinkov, Yonatan
%Y Dupoux, Emmanuel
%Y Giulianelli, Mario
%Y Hupkes, Dieuwke
%Y Pinter, Yuval
%Y Sajjad, Hassan
%S Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F ryskina-knight-2021-learning
%X Embedding words in high-dimensional vector spaces has proven valuable in many natural language applications. In this work, we investigate whether similarly-trained embeddings of integers can capture concepts that are useful for mathematical applications. We probe the integer embeddings for mathematical knowledge, apply them to a set of numerical reasoning tasks, and show that by learning the representations from mathematical sequence data, we can substantially improve over number embeddings learned from English text corpora.
%R 10.18653/v1/2021.blackboxnlp-1.30
%U https://aclanthology.org/2021.blackboxnlp-1.30
%U https://doi.org/10.18653/v1/2021.blackboxnlp-1.30
%P 389-395

Markdown (Informal)

[Learning Mathematical Properties of Integers](https://aclanthology.org/2021.blackboxnlp-1.30) (Ryskina & Knight, BlackboxNLP 2021)

• Learning Mathematical Properties of Integers (Ryskina & Knight, BlackboxNLP 2021)

ACL

• Maria Ryskina and Kevin Knight. 2021. Learning Mathematical Properties of Integers. In Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pages 389–395, Punta Cana, Dominican Republic. Association for Computational Linguistics.