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dc.contributor.authorDalal, Dhairya
dc.contributor.authorArcan, Mihael
dc.contributor.authorBuitelaar, Paul
dc.identifier.citationDalal, Dhairya, Arcan, Mihael, & Buitelaar, Paul. (2021). Enhancing multiple-choice question answering with causal knowledge. Paper presented at the Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, Online, 10 June. doi:10.18653/v1/2021.deelio-1.8en_IE
dc.description.abstractThe task of causal question answering aims to reason about causes and effects over a provided real or hypothetical premise. Recent approaches have converged on using transformer-based language models to solve question answering tasks. However, pretrained language models often struggle when external knowledge is not present in the premise or when additional context is required to answer the question. To the best of our knowledge, no prior work has explored the efficacy of augmenting pretrained language models with external causal knowledge for multiple-choice causal question answering. In this paper, we present novel strategies for the representation of causal knowledge. Our empirical results demonstrate the efficacy of augmenting pretrained models with external causal knowledge. We show improved performance on the COPA (Choice of Plausible Alternatives) and WIQA (What If Reasoning Over Procedural Text) benchmark tasks. On the WIQA benchmark, our approach is competitive with the state-of-the-art and exceeds it within the evaluation subcategories of In-Paragraph and Out-of-Paragraph perturbations.en_IE
dc.description.sponsorshipThis work was supported by Science Foundation Ireland under grants SFI/18/CRT/6223 (Centre for Research Training in Artificial Intelligence) and SFI/12/RC/2289_P2 (Insight), co-funded by the European Regional Development Fund.en_IE
dc.publisherAssociation for Computational Linguisticsen_IE
dc.relation.ispartofProceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architecturesen
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.subjectMultiple-Choice Question Answeringen_IE
dc.subjectCausal Knowledgeen_IE
dc.subjectData scienceen_IE
dc.titleEnhancing multiple-choice question answering with causal knowledgeen_IE
dc.typeWorkshop paperen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderEuropean Regional Development Funden_IE
dc.local.contactDhairya Dalal. Email:
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE

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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)