arxivcs.LG2026-07-09
Contrastive Order Learning: A General Framework for Ordinal Regression
Chaewon Lee, BeomJun Shim, Kwang Pyo Choi, Chang-Su Kim
We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. While contrastive learning effectively leverages all samples in a batch, it typically ignores the inhe…