Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop

Research output: Contribution to journalArticleScientific

Abstract

The Empirical Methods in Natural Language Processing (EMNLP) 2018 workshop BlackboxNLP was dedicated to resources and techniques specifically developed for analyzing and understanding the inner-workings and representations acquired by neural models of language. Approaches included: systematic manipulation of input to neural networks and investigating the impact on their performance, testing whether interpretable knowledge can be decoded from intermediate representations acquired by neural networks, proposing modifications to neural network architectures to make their knowledge state or generated output more explainable, and examining the performance of networks on simplified or formal languages. Here we review a number of representative studies in each category.

Original languageEnglish
Article number135132491900024
Pages (from-to)543-557
Number of pages15
JournalNatural Language Engineering
Volume25
Issue number4
DOIs
Publication statusPublished - 31 Jul 2019
Event2018 EMNLP BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP - Brussels, Belgium
Duration: 1 Nov 20181 Nov 2018
Conference number: 1
https://blackboxnlp.github.io/2018/

Keywords

  • RECURRENT
  • interpretability
  • natural language processing
  • neural networks

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