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        <title>Patterns of Text Readability in Human and Predicted Eye Movements</title>
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        <namePart type="given">Nora</namePart>
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    <name type="personal">
        <namePart type="given">Itziar</namePart>
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    <name type="personal">
        <namePart type="given">Lena</namePart>
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            <title>Proceedings of the Workshop on Cognitive Aspects of the Lexicon</title>
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        <name type="personal">
            <namePart type="given">Michael</namePart>
            <namePart type="family">Zock</namePart>
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        <name type="personal">
            <namePart type="given">Emmanuele</namePart>
            <namePart type="family">Chersoni</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Yu-Yin</namePart>
            <namePart type="family">Hsu</namePart>
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        <name type="personal">
            <namePart type="given">Enrico</namePart>
            <namePart type="family">Santus</namePart>
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    <abstract>It has been shown that multilingual transformer models are able to predict human reading behavior when fine-tuned on small amounts of eye tracking data. As the cumulated prediction results do not provide insights into the linguistic cues that the model acquires to predict reading behavior, we conduct a deeper analysis of the predictions from the perspective of readability. We try to disentangle the three-fold relationship between human eye movements, the capability of language models to predict these eye movement patterns, and sentence-level readability measures for English. We compare a range of model configurations to multiple baselines. We show that the models exhibit difficulties with function words and that pre-training only provides limited advantages for linguistic generalization.</abstract>
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    <identifier type="doi">10.18653/v1/2022.cogalex-1.1</identifier>
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%0 Conference Proceedings
%T Patterns of Text Readability in Human and Predicted Eye Movements
%A Hollenstein, Nora
%A Gonzalez-Dios, Itziar
%A Beinborn, Lisa
%A Jäger, Lena
%Y Zock, Michael
%Y Chersoni, Emmanuele
%Y Hsu, Yu-Yin
%Y Santus, Enrico
%S Proceedings of the Workshop on Cognitive Aspects of the Lexicon
%D 2022
%8 November
%I Association for Computational Linguistics
%C Taipei, Taiwan
%F hollenstein-etal-2022-patterns
%X It has been shown that multilingual transformer models are able to predict human reading behavior when fine-tuned on small amounts of eye tracking data. As the cumulated prediction results do not provide insights into the linguistic cues that the model acquires to predict reading behavior, we conduct a deeper analysis of the predictions from the perspective of readability. We try to disentangle the three-fold relationship between human eye movements, the capability of language models to predict these eye movement patterns, and sentence-level readability measures for English. We compare a range of model configurations to multiple baselines. We show that the models exhibit difficulties with function words and that pre-training only provides limited advantages for linguistic generalization.
%R 10.18653/v1/2022.cogalex-1.1
%U https://aclanthology.org/2022.cogalex-1.1/
%U https://doi.org/10.18653/v1/2022.cogalex-1.1
%P 1-15

Markdown (Informal)

[Patterns of Text Readability in Human and Predicted Eye Movements](https://aclanthology.org/2022.cogalex-1.1/) (Hollenstein et al., CogALex 2022)

• Patterns of Text Readability in Human and Predicted Eye Movements (Hollenstein et al., CogALex 2022)

ACL

• Nora Hollenstein, Itziar Gonzalez-Dios, Lisa Beinborn, and Lena Jäger. 2022. Patterns of Text Readability in Human and Predicted Eye Movements. In Proceedings of the Workshop on Cognitive Aspects of the Lexicon, pages 1–15, Taipei, Taiwan. Association for Computational Linguistics.