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Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differences

Haller, Patrick; Bolliger, Lena Sophia; Jäger, Lena A (2024). Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differences. In: The 62nd Annual Meeting of the Association for Computational Linguistics, Bangkok, Thailand, 11 August 2024 - 16 August 2024. Association for Computational Linguistics, 7878-7892.

Abstract

To date, most investigations on surprisal and entropy effects in reading have been conducted on the group level, disregarding individual differences. In this work, we revisit the predictive power (PP) of different LMs’ surprisal and entropy measures on data of human reading times as a measure of processing effort by incorporating information of language users’ cognitive capacities. To do so, we assess the PP of surprisal and entropy estimated from generative language models (LMs) on reading data obtained from individuals who also completed a wide range of psychometric tests.Specifically, we investigate if modulating surprisal and entropy relative to cognitive scores increases prediction accuracy of reading times, and we examine whether LMs exhibit systematic biases in the prediction of reading times for cognitively high- or low-performing groups, revealing what type of psycholinguistic subjects a given LM emulates.Our study finds that in most cases, incorporating cognitive capacities increases predictive power of surprisal and entropy on reading times, and that generally, high performance in the psychometric tests is associated with lower sensitivity to predictability effects. Finally, our results suggest that the analyzed LMs emulate readers with lower verbal intelligence, suggesting that for a given target group (i.e., individuals with high verbal intelligence), these LMs provide less accurate predictability effect estimates.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:16 August 2024
Deposited On:06 Jan 2025 08:45
Last Modified:28 Jan 2025 06:04
Publisher:Association for Computational Linguistics
Series Name:Findings of the Association for Computational Linguistics
Number:62
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.18653/v1/2024.findings-acl.469
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  • Licence: Creative Commons: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)

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