A Psycholinguistic Evaluation of Language Models' Sensitivity to Argument Roles
Abstract: We present a systematic evaluation of large language models' sensitivity to argument roles, i.e., $\textit{who}$ did what to $\textit{whom}$, by replicating psycholinguistic studies on human argument role processing. In three experiments, we find that language models are able to distinguish verbs that appear in plausible and implausible contexts, where plausibility is determined through the relation between the verb and its preceding arguments. However, none of the models capture the same selective patterns that human comprehenders exhibit during real-time verb prediction. This indicates that language models' capacity to detect verb plausibility does not arise from the same mechanism that underlies human real-time sentence processing.
Paper Type: Long
Research Area: Linguistic theories, Cognitive Modeling and Psycholinguistics
Research Area Keywords: linguistic theories; cognitive modeling; computational psycholinguistics
Contribution Types: Model analysis & interpretability, Data analysis
Languages Studied: English
Submission Number: 3099
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