MATH · IN · MODELS

Semantic projection onto antonym-pole directions recovers human feature ratings

measured in 1 paper

Grand et al. define 52 bipolar feature lines as the vector difference between antonym-pole words in real 300-d GloVe (42B Common Crawl) [grand-etal-2022-semantic-projection] Category members (animals, cities, professions) are scored by their scalar projection onto each line [grand-etal-2022-semantic-projection] Projection scores correlate with human graded ratings at median Pearson r=0.47 (reliability-adjusted median 0.61) [grand-etal-2022-semantic-projection] Single-pole-only controls perform far worse (r=0.18 and r=0), validating the two-pole direction against external ground truth; no causal intervention [grand-etal-2022-semantic-projection]

Context

semantic projection, bipolar feature direction, antonym-pole vector difference

Papers

Semantic Projection Recovers Rich Human Knowledge of Multiple Object Features from Word Embeddings — Grand, Gabriel, Blank, Idan A., Pereira, Francisco, Fedorenko, Evelina2022 · arXiv:1802.01241