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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 10: AAAI-22 Technical Tracks 10

Flexible Instance-Specific Rationalization of NLP Models

February 1, 2023

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Authors

George Chrysostomou

University of Sheffield


Nikolaos Aletras

University of Sheffield


DOI:

10.1609/aaai.v36i10.21298


Abstract:

Recent research on model interpretability in natural language processing extensively uses feature scoring methods for identifying which parts of the input are the most important for a model to make a prediction (i.e. explanation or rationale). However, previous research has shown that there is no clear best scoring method across various text classification tasks while practitioners typically have to make several other ad-hoc choices regarding the length and the type of the rationale (e.g. short or long, contiguous or not). Inspired by this, we propose a simple yet effective and flexible method that allows selecting optimally for each data instance: (1) a feature scoring method; (2) the length; and (3) the type of the rationale. Our method is inspired by input erasure approaches to interpretability which assume that the most faithful rationale for a prediction should be the one with the highest difference between the model's output distribution using the full text and the text after removing the rationale as input respectively. Evaluation on four standard text classification datasets shows that our proposed method provides more faithful, comprehensive and highly sufficient explanations compared to using a fixed feature scoring method, rationale length and type. More importantly, we demonstrate that a practitioner is not required to make any ad-hoc choices in order to extract faithful rationales using our approach.

Topics: AAAI

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HOW TO CITE:

George Chrysostomou||Nikolaos Aletras Flexible Instance-Specific Rationalization of NLP Models Proceedings of the AAAI Conference on Artificial Intelligence (2022) 10545-10553.

George Chrysostomou||Nikolaos Aletras Flexible Instance-Specific Rationalization of NLP Models AAAI 2022, 10545-10553.

George Chrysostomou||Nikolaos Aletras (2022). Flexible Instance-Specific Rationalization of NLP Models. Proceedings of the AAAI Conference on Artificial Intelligence, 10545-10553.

George Chrysostomou||Nikolaos Aletras. Flexible Instance-Specific Rationalization of NLP Models. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.10545-10553.

George Chrysostomou||Nikolaos Aletras. 2022. Flexible Instance-Specific Rationalization of NLP Models. "Proceedings of the AAAI Conference on Artificial Intelligence". 10545-10553.

George Chrysostomou||Nikolaos Aletras. (2022) "Flexible Instance-Specific Rationalization of NLP Models", Proceedings of the AAAI Conference on Artificial Intelligence, p.10545-10553

George Chrysostomou||Nikolaos Aletras, "Flexible Instance-Specific Rationalization of NLP Models", AAAI, p.10545-10553, 2022.

George Chrysostomou||Nikolaos Aletras. "Flexible Instance-Specific Rationalization of NLP Models". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.10545-10553.

George Chrysostomou||Nikolaos Aletras. "Flexible Instance-Specific Rationalization of NLP Models". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 10545-10553.

George Chrysostomou||Nikolaos Aletras. Flexible Instance-Specific Rationalization of NLP Models. AAAI[Internet]. 2022[cited 2023]; 10545-10553.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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