ArticleNature human behaviour2025
Large language models without grounding recover non-sensorimotor but not sensorimotor features of human concepts.
Article in Nature human behaviour, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Contextualized sensorimotor norms: Multi-dimensional measures of sensorimotor strength for ambiguous English words, in context.Behavior research methods · 2026Article
- Large Language Models Estimate Fine-Grained Human Color-Concept Associations.Cognitive science · 2026Article
- Constituent-constrained word prediction during language comprehension.Nature neuroscience · 2026Article
- Cortical knowledge structures guide word concept learning.Nature communications · 2026Article
- Semantic convergence in culturally loaded text translation by Large Language Models: a cross-model empirical analysis of English translations ofFrontiers in psychology · 2026Article
- Conceptual blending in humans and language models.Frontiers in psychology · 2026Review
- ISEED: an always-on cognitive architecture for experience-driven interaction-oriented humanoid robots.Frontiers in neurorobotics · 2026Article
- Contextual assembly of lexical functions in large language models.Behavior research methods · 2025Article
- Refining the multimodality of semantic representations.Trends in cognitive sciences · 2025Article
- Lexical Representations in the Common and Specific Neural Networks for Visual, Phonological, and Semantic Processing in Chinese Reading.Human brain mapping · 2025Article
- Increasing alignment of large language models with language processing in the human brain.Nature computational science · 2025Article
- Distinctive Human Dynamics of Semantic Uncertainty: Contextual Bias Accelerates Lexical Disambiguation.Behavioral sciences (Basel, Switzerland) · 2025Article
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6 authors.
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Abstract
To what extent can language give rise to complex conceptual representation? Is multisensory experience essential? Recent large language models (LLMs) challenge the necessity of grounding for concept formation: whether LLMs without grounding nevertheless exhibit human-like representations. Here we compare multidimensional representations of ~4,442 lexical concepts between humans (the Glasgow Norms
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