Rationalization for explainable NLP: a survey

Recent advances in deep learning have improved the performance of many Natural Language Processing (NLP) tasks such as translation, question-answering, and text classification. However, this improvement comes at the expense of model explainability. Black-box models make it difficult to understand th...

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Bibliographic Details
Published in:	Frontiers in Artificial Intelligence
Main Authors:	Sai Gurrapu, Ajay Kulkarni, Lifu Huang, Ismini Lourentzou, Feras A. Batarseh
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2023-09-01
Subjects:	rationalization explainable NLP rationales abstractive rationale extractive rationale large language models
Online Access:	https://www.frontiersin.org/articles/10.3389/frai.2023.1225093/full

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