The paper derives a constant-additional-risk condition for label-noise robustness of any contrastive loss and proposes SymNCE, an InfoNCE variant that meets this condition in the infinite-sample limit.
Neural information retrieval: at the end of the early years,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
The paper derives a constant-additional-risk condition for label-noise robustness of any contrastive loss and proposes SymNCE, an InfoNCE variant that meets this condition in the infinite-sample limit.