Analysis Methods in Neural Language Processing: A Survey | Zendy

Yonatan Belinkov | Zendy; James Glass | Zendy

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Analysis Methods in Neural Language Processing: A Survey

Author(s) -

Yonatan Belinkov,

James Glass

Publication year - 2019

Publication title -

transactions of the association for computational linguistics

Language(s) - English

Resource type - Journals

ISSN - 2307-387X

DOI - 10.1162/tacl_a_00254

Subject(s) - computer science , categorization , artificial neural network , field (mathematics) , feature (linguistics) , artificial intelligence , point (geometry) , data science , natural language processing , machine learning , linguistics , philosophy , geometry , mathematics , pure mathematics

The field of natural language processing has seen impressive progress in recent years, with neural network models replacing many of the traditional systems. A plethora of new models have been proposed, many of which are thought to be opaque compared to their feature-rich counterparts. This has led researchers to analyze, interpret, and evaluate neural networks in novel and more fine-grained ways. In this survey paper, we review analysis methods in neural language processing, categorize them according to prominent research trends, highlight existing limitations, and point to potential directions for future work.

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