Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Consistency of augmentation graph and network approximability in contrastive learning
Chenghui Li, A. Martina Neuman
Contrastive learning leverages data augmentation to develop feature representation without relying on large labeled datasets. However, despite its empirical success, the theoretica…
cs.LG2025
Quantifying Structure in CLIP Embeddings: A Statistical Framework for Concept Interpretation
Jitian Zhao, Chenghui Li, Frederic Sala +1
Concept-based approaches, which aim to identify human-understandable concepts within a model's internal representations, are a promising method for interpreting embeddings from dee…