ArticleNature human behaviour2022
Semantic projection recovers rich human knowledge of multiple object features from word embeddings.
Article in Nature human behaviour, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed, 168 citations in OpenAlex.
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- Measuring Psychological Constructs from Social Media Text Using the Word Embedding Projection Approach.Behavioral sciences (Basel, Switzerland) · 2026Article
- Ousiometrics: The essence of meaning aligns with a power-danger-structure framework instead of valence-arousal-dominance.Science advances · 2026Article
- A neural network for modeling human concept formation, understanding and communication.Nature computational science · 2026Article
- Semantic similarity across languages reflects neurocognitive dimensions shaped by climate.Nature communications · 2026Article
- Natural language reveals that political partisans are more affectively aligned over political issues than partisan identities.Communications psychology · 2026Article
- What makes memories vivid?Journal of experimental psychology. General · 2026Article
- Deciphering the 3D genome organization across species from Hi-C data.Nucleic acids research · 2026Article
- Beyond redundancy: rethinking construct proliferation through meaning, practice, and taxonomy.Frontiers in psychology · 2026Article
- Anchoring race: improving the construction of race dimensions in word embeddings.Journal of computational social science · 2026Article
- Do Language Models Know Who Did What to Whom?Open mind : discoveries in cognitive science · 2026Article
- Semantic projection as a method to measure individual differences in semantic scale length: insights from autism-related traits.Scientific reports · 2025Article
- Revealing emergent human-like conceptual representations from language prediction.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Associating everything with everything else, all at once: Semantic associations facilitate visual working memory formation for real-world objects.Journal of experimental psychology. Human perception and performance · 2025Article
- Uncovering patterns of semantic predictability in sentence processing.Journal of memory and language · 2025Article
- Large language models without grounding recover non-sensorimotor but not sensorimotor features of human concepts.Nature human behaviour · 2025Article
- Leveraging Context for Perceptual Prediction Using Word Embeddings.Cognitive science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 1 country.
Funding
Abstract
How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein words that are used in more similar linguistic contexts-that is, are more semantically related-are located closer together. However, whereas inter-word proximity captures only overall relatedness, human judgements are highly context dependent. For example, dolphins and alligators are similar in size but differ in dangerousness. Here, we use a domain-general method to extract context-dependent relationships from word embeddings: 'semantic projection' of word-vectors onto lines that represent features such as size (the line connecting the words 'small' and 'big') or danger ('safe' to 'dangerous'), analogous to 'mental scales'. This method recovers human judgements across various object categories and properties. Thus, the geometry of word embeddings explicitly represents a wealth of context-dependent world knowledge.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.