arXiv cs.AI
· Papers
XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision
arXiv:2601.21688v2 Announce Type: replace-cross Abstract: Disentangled representation learning aims to map independent factors of variation to independent representation components. On one hand, purely unsupervised approaches have proven successful on fully disentangled synthetic data, but fail to recover semantic fact