From: NeurIPS.cc/2021/Workshop/DistShift/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: The paper discusses generalization across domains in vehicle intent prediction. This is a relevant but unstudied application in the domain generalization literature, and will be of interest to the workshop audience. 

However, both reviewers raised concerns about the lack of clarity in the mathematical exposition, which will make it difficult for readers to follow. We strongly urge the authors to take their feedback into account for the revision.

Other comments:
1. The gap between FT and ZS accuracies need not be due to the domain shift. Instead, ZS could just be intrinsically harder: maybe if we trained on ZS and tested on ZS, the accuracy would still be lower. Could the authors evaluate this?
2. How significant are the differences in the performance across algorithms? The error bars on some of the numbers seem very high.