CogNLP-Sheffield at CMCL 2021 Shared Task: Blending cognitively inspired features with transformer-based language models for predicting eye tracking patterns

Vickers, P., Wainwright, R., Tayyar Madabushi, H. et al. (1 more author) (2021) CogNLP-Sheffield at CMCL 2021 Shared Task: Blending cognitively inspired features with transformer-based language models for predicting eye tracking patterns. In: Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2021). Cognitive Modeling and Computational Linguistics (CMCL 2021), 10 Jun 2021, Mexico City, Mexico. Association for Computational Linguistics (ACL) , pp. 125-133. ISBN 9781954085350

Abstract

The CogNLP-Sheffield submissions to the CMCL 2021 Shared Task examine the value of a variety of cognitively and linguistically inspired features for predicting eye tracking patterns, as both standalone model inputs and as supplements to contextual word embeddings (XLNet). Surprisingly, the smaller pre-trained model (XLNet-base) outperforms the larger (XLNet-large), and despite evidence that multi-word expressions (MWEs) provide cognitive processing advantages, MWE features provide little benefit to either model.

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Item Type:	Proceedings Paper
Authors/Creators:	Vickers, P. Wainwright, R. Tayyar Madabushi, H. Villavicencio, A. https://orcid.org/0000-0002-3731-9168
Copyright, Publisher and Additional Information:	© 2021 The Authors. Licensed on a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
Dates:	Published: June 2021 Published (online): June 2021 Accepted: 30 April 2021
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:	Funder Grant number Engineering and Physical Science Research Council EP/T02450X/1; 2269013 The Royal Society NAF\R2\202209
Depositing User:	Symplectic Sheffield
Date Deposited:	07 May 2021 11:51
Last Modified:	01 Feb 2022 18:08
Status:	Published
Publisher:	Association for Computational Linguistics (ACL)
Refereed:	Yes
Identification Number:	10.18653/v1/2021.cmcl-1.16
Related URLs:	Conference
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:173802

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CogNLP-Sheffield at CMCL 2021 Shared Task: Blending cognitively inspired features with transformer-based language models for predicting eye tracking patterns

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