Research Area:  Machine Learning

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.

Keywords:  

Author(s) Name:  Yonatan Belinkov, James Glass

Publisher name:  The ACL Anthology

DOI:  10.1162/tacl_a_00254

Volume Information:  Vol 7, Q19-1004, pp 49-72

Paper Link:   https://aclanthology.org/Q19-1004/