25 citations · 25 across the 1 of their papers we have counts for
2 papers
cs.LG2021★ 25 cited
Improving Multi-Modal Learning with Uni-Modal Teachers
Chenzhuang Du, Tingle Li, Yichen Liu +4
Learning multi-modal representations is an essential step towards real-world robotic applications, and various multi-modal fusion models have been developed for this purpose. Howev…
cs.LG2021
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
How can neural networks trained by contrastive learning extract features from the unlabeled data? Why does contrastive learning usually need much stronger data augmentations than s…