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        <title>Exploring Spatial Schema Intuitions in Large Language and Vision Models</title>
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    <abstract>Despite the ubiquity of large language models (LLMs) in AI research, the question of embodiment in LLMs remains underexplored, distinguishing them from embodied systems in robotics where sensory perception directly informs physical action.Our investigation navigates the intriguing terrain of whether LLMs, despite their non-embodied nature, effectively capture implicit human intuitions about fundamental, spatial building blocks of language. We employ insights from spatial cognitive foundations developed through early sensorimotor experiences, guiding our exploration through the reproduction of three psycholinguistic experiments. Surprisingly, correlations between model outputs and human responses emerge, revealing adaptability without a tangible connection to embodied experiences. Notable distinctions include polarized language model responses and reduced correlations in vision language models. This research contributes to a nuanced understanding of the interplay between language, spatial experiences, and the computations made by large language models.Project Website: https://cisnlp.github.io/Spatial_Schemas/</abstract>
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%0 Conference Proceedings
%T Exploring Spatial Schema Intuitions in Large Language and Vision Models
%A Wicke, Philipp
%A Wachowiak, Lennart
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand and virtual meeting
%F wicke-wachowiak-2024-exploring
%X Despite the ubiquity of large language models (LLMs) in AI research, the question of embodiment in LLMs remains underexplored, distinguishing them from embodied systems in robotics where sensory perception directly informs physical action.Our investigation navigates the intriguing terrain of whether LLMs, despite their non-embodied nature, effectively capture implicit human intuitions about fundamental, spatial building blocks of language. We employ insights from spatial cognitive foundations developed through early sensorimotor experiences, guiding our exploration through the reproduction of three psycholinguistic experiments. Surprisingly, correlations between model outputs and human responses emerge, revealing adaptability without a tangible connection to embodied experiences. Notable distinctions include polarized language model responses and reduced correlations in vision language models. This research contributes to a nuanced understanding of the interplay between language, spatial experiences, and the computations made by large language models.Project Website: https://cisnlp.github.io/Spatial_Schemas/
%U https://aclanthology.org/2024.findings-acl.365
%P 6102-6117

Markdown (Informal)

[Exploring Spatial Schema Intuitions in Large Language and Vision Models](https://aclanthology.org/2024.findings-acl.365) (Wicke & Wachowiak, Findings 2024)

• Exploring Spatial Schema Intuitions in Large Language and Vision Models (Wicke & Wachowiak, Findings 2024)

ACL

• Philipp Wicke and Lennart Wachowiak. 2024. Exploring Spatial Schema Intuitions in Large Language and Vision Models. In Findings of the Association for Computational Linguistics ACL 2024, pages 6102–6117, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.