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INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations

Yu, Jialin; Cristea, Alexandra I.; Harit, Anoushka; Sun, Zhongtian; Aduragba, Olanrewaju Tahir; Shi, Lei; Al Moubayed, Noura

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Jialin Yu
Academic Visitor

Zhongtian Sun

Lei Shi


XAI with natural language processing aims to produce human-readable explanations as evidence for AI decisionmaking, which addresses explainability and transparency. However, from an HCI perspective, the current approaches only focus on delivering a single explanation, which fails to account for the diversity of human thoughts and experiences in language. This paper thus addresses this gap, by proposing a generative XAI framework, INTERACTION (explaIn aNd predicT thEn queRy with contextuAl CondiTional varIational autO-eNcoder). Our novel framework presents explanation in two steps: (step one) Explanation and Label Prediction; and (step two) Diverse Evidence Generation. We conduct intensive experiments with the Transformer architecture on a benchmark dataset, e-SNLI [1]. Our method achieves competitive or better performance against state-of-the-art baseline models on explanation generation (up to 4.7% gain in BLEU) and prediction (up to 4.4% gain in accuracy) in step one


Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2022). INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations. .

Conference Name 2022 International Joint Conference on Neural Networks (IJCNN)
Conference Location Padova, Italy
Start Date Jul 18, 2022
End Date Jul 23, 2022
Acceptance Date Apr 26, 2022
Online Publication Date Sep 30, 2022
Publication Date 2022
Deposit Date Aug 31, 2022
Publicly Available Date Sep 1, 2022
Series ISSN 2161-4393,2161-4407


Accepted Conference Proceeding (498 Kb)

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