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VIDEO DOI: https://doi.org/10.48448/q202-x293

poster

ACL 2024

August 13, 2024

Bangkok, Thailand

Measuring Meaning Composition in the Human Brain with Composition Scores from Large Language Models

keywords:

composition score

meaning composition

large language model

fmri

The process of meaning composition, wherein smaller units like morphemes or words combine to form the meaning of phrases and sentences, is essential for human sentence comprehension. Despite extensive neurolinguistic research into the brain regions involved in meaning composition, a computational metric to quantify the extent of composition is still lacking. Drawing on the key-value memory interpretation of transformer feed-forward network blocks, we introduce the Composition Score, a novel model-based metric designed to quantify the degree of meaning composition during sentence comprehension. Experimental findings show that this metric correlates with brain clusters associated with word frequency, structural processing, and general sensitivity to words, suggesting the multifaceted nature of meaning composition during human sentence comprehension.

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Transcript English (automatic)

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