From: NeurIPS.cc/2021/Workshop/DistShift/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: The paper combines two established approaches (consistency regularization and contrastive learning) for the problem of semi-supervised domain adaptation (when a few labeled samples are available from the target set, as well as unlabeled target data). The experimental results are promising despite not being clearly better than the baselines. Having said that, the reviewers agree that the experimental comparison is extensive and sound and that the combination of the two semi-supervised techniques could be of interest to the community. Therefore, we accept the paper and encourage the authors to address the reviewers’ feedback.

(Note: the citation for MME in Table 1 is incorrect, should be [28], I believe)