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Analysis Methods in Neural Language Processing: A Survey
2019
Transactions of the Association for Computational Linguistics
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 featurerich 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
doi:10.1162/tacl_a_00254
fatcat:unfqn4wpmvbofbsuv46djwlm7e