A Survey of the State of Explainable AI for Natural Language Processing

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Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, Prithviraj Sen. Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing. 2020.

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Marina Danilevsky

IBM (United States)

Kun Qian

Uppsala University

Ranit Aharonov

Ernst & Young (Israel)

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IBM (United States)

IBM Research - Almaden

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Danilevsky et al. (Wed,) studied this question.

synapsesocial.com/papers/6a02b39198cafe0df57552f0 — DOI: https://doi.org/10.18653/v1/2020.aacl-main.46

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

"Why Should I Trust You?"· 2016 · 15,080 citations
Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach· 2019 · 21 citations
QUINT: Interpretable Question Answering over Knowledge Bases· 2017 · 48 citations
On Interpretation of Network Embedding via Taxonomy Induction· 2018 · 56 citations
Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications· 2019 · 68 citations

A Survey of the State of Explainable AI for Natural Language Processing

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Abstract

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Cite this study

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