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Multilingual Language Models Predict Human Reading Behavior ...
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Abstract:
We analyze if large language models are able to predict patterns of human reading behavior. We compare the performance of language-specific and multilingual pretrained transformer models to predict reading time measures reflecting natural human sentence processing on Dutch, English, German, and Russian texts. This results in accurate models of human reading behavior, which indicates that transformer models implicitly encode relative importance in language in a way that is comparable to human processing mechanisms. We find that BERT and XLM models successfully predict a range of eye tracking features. In a series of experiments, we analyze the cross-domain and cross-language abilities of these models and show how they reflect human sentence processing. ... : accepted at NAACL 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2104.05433 https://arxiv.org/abs/2104.05433
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Multilingual Language Models Predict Human Reading Behavior ...
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Multilingual language models predict human reading behavior ...
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Multilingual Language Models Predict Human Reading Behavior ...
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Antecedent access mechanisms in pronoun processing ... : evidence from the N400 ...
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Antecedent access mechanisms in pronoun processing: evidence from the N400 ...
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Antecedent access mechanisms in pronoun processing: evidence from the N400 ...
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Overt language production of German past participles: investigating (ir-)regularity ...
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Overt language production of German past participles: investigating (ir-)regularity ...
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A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements ...
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Feature overwriting as a finite mixture process: Evidence from comprehension data ...
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The effect of prominence and cue association in retrieval processes: A computational account ...
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