Supervised dataset discrimination overstates semantic bias via resolution artifacts; unsupervised clustering of foundation-model features on web-scale datasets yields near-chance separability.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
What Are We Really Measuring? Rethinking Dataset Bias in Web-Scale Natural Image Collections via Unsupervised Semantic Clustering
Supervised dataset discrimination overstates semantic bias via resolution artifacts; unsupervised clustering of foundation-model features on web-scale datasets yields near-chance separability.