Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models (P19-1)
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| Challenge: | Existing studies have shown that distributional semantic models can be used to decode fMRI patterns associated with specific aspects of semantic composition, such as the negation function. |
| Approach: | They apply lexical and compositional semantic models to decode fMRI patterns associated with negated and affirmative sentences containing hand-action verbs. |
| Outcome: | The proposed models show reduced decoding of sentences where the verb is in the negated context, as compared to the affirmative one, within brain regions implicated in action-semantic processing. |
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| Challenge: | Recent studies on hallucination in large language models (LLMs) have been actively progressing in natural language processing. |
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