@article{belinkov-glass-2019-analysis,
title = "Analysis Methods in Neural Language Processing: A Survey",
author = "Belinkov, Yonatan and
Glass, James",
editor = "Lee, Lillian and
Johnson, Mark and
Roark, Brian and
Nenkova, Ani",
journal = "Transactions of the Association for Computational Linguistics",
volume = "7",
year = "2019",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/Q19-1004",
doi = "10.1162/tacl_a_00254",
pages = "49--72",
abstract = "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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%0 Journal Article
%T Analysis Methods in Neural Language Processing: A Survey
%A Belinkov, Yonatan
%A Glass, James
%J Transactions of the Association for Computational Linguistics
%D 2019
%V 7
%I MIT Press
%C Cambridge, MA
%F belinkov-glass-2019-analysis
%X 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.
%R 10.1162/tacl_a_00254
%U https://aclanthology.org/Q19-1004
%U https://doi.org/10.1162/tacl_a_00254
%P 49-72
Markdown (Informal)
[Analysis Methods in Neural Language Processing: A Survey](https://aclanthology.org/Q19-1004) (Belinkov & Glass, TACL 2019)
ACL