Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/120093
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Language Science and Technology | en_US |
| dc.creator | Wang, Y | en_US |
| dc.creator | Chersoni, E | en_US |
| dc.creator | Huang, CR | en_US |
| dc.date.accessioned | 2026-07-22T08:13:10Z | - |
| dc.date.available | 2026-07-22T08:13:10Z | - |
| dc.identifier.isbn | 979-8-89176-390-6 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/120093 | - |
| dc.description | The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), San Diego, California, United States, July 2-7, 2026 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Association for Computational Linguistics | en_US |
| dc.rights | ©2026 Association for Computational Linguistics | en_US |
| dc.rights | Licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) | en_US |
| dc.rights | The following publication Wang, Y., Chersoni, E., & Huang, C.-R. (2026a). Do LLMS capture embodied cognition and cultural variation? cross-linguistic evidence from demonstratives. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 10158–10174 is available at https://doi.org/10.18653/v1/2026.acl-long.461. | en_US |
| dc.title | Do LLMs capture embodied cognition and cultural variation? Cross-linguistic evidence from demonstratives | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.spage | 10158 | en_US |
| dc.identifier.epage | 10174 | en_US |
| dc.identifier.doi | 10.18653/v1/2026.acl-long.461 | en_US |
| dcterms.abstract | Do large language models (LLMs) truly acquire embodied cognition and cultural conventions from text? We introduce demonstratives—fundamental spatial expressions like “this/that” in English and “这/那” in Chinese—as a novel probe for grounded knowledge. Using 6,400 responses from 320 native speakers, we establish a human baseline: English speakers reliably distinguish proximal–distal referents but struggle with perspective-taking, while Chinese speakers switch perspectives fluently but tolerate distal ambiguity. In contrast, five state-of-the-art LLMs fail to inherently understand the proximal–distal contrast and show no cultural differences, defaulting to English-centric reasoning. Our study contributes (i) a new task, based on demonstratives, as a lens for evaluating embodied cognition and cultural conventions; (ii) empirical evidence of cross-cultural asymmetries in human interpretation; (iii) a new perspective on the egocentric–sociocentric debate, showing both orientations coexist but vary across languages; and (iv) a call to address individual variation in future model design. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | In 64th Annual Meeting of the Association for Computational Linguistic: Proceedings of the Conference Vol. 1 (Long Papers), p. 10158-10174. Kerrville : Association for Computational Linguistics(ACL), 2026 | en_US |
| dcterms.issued | 2026 | - |
| dc.relation.ispartofbook | Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) | en_US |
| dc.relation.conference | Annual Meeting of the Association for Computational Linguistics | en_US |
| dc.description.validate | 202607 bcwc | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | a4672 | - |
| dc.identifier.SubFormID | 53571 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingText | EC was supported by a GRF grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 15601325). | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Conference Paper | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2026.acl-long.461.pdf | 442.24 kB | Adobe PDF | View/Open |
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