A Psycholinguistic Evaluation of Language Models' Sensitivity to Argument Roles

• URL: http://arxiv.org/abs/2410.16139v1
• Date: Mon, 21 Oct 2024 16:05:58 GMT
• Title: A Psycholinguistic Evaluation of Language Models' Sensitivity to Argument Roles
• Authors: Eun-Kyoung Rosa Lee, Sathvik Nair, Naomi Feldman,
• Abstract summary: We evaluate large language models' sensitivity to argument roles by replicating psycholinguistic studies on human argument role processing. 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. This indicates that language models' capacity to detect verb plausibility does not arise from the same mechanism that underlies human real-time sentence processing.
• Score: 0.06554326244334868
• License:
• Abstract: We present a systematic evaluation of large language models' sensitivity to argument roles, i.e., who did what to 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.

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