arXiv stat.ML
· Papers
Similarity search generalisation in contrastive learning with InfoNCE loss
arXiv:2607.09405v1 Announce Type: cross Abstract: Similarity search is a primary application of embedding models trained by contrastive learning. For one of the most popular contrastive learning loss functions, InfoNCE, we show that the population risk with $k$ negative samples is $O(1/k)$ close to an expected cross-en