This week Knarik Mheryan from YerevaNN will present a paper from EMNLP 2021 - Model Selection for Cross-lingual Transfer
. In the traditional zero-shot cross-lingual transfer there's no access to development/validation data (otherwise we could always train on dev data instead of zero-shot transfer and get consistently better results). The trivial approach is to use the source language dev set, but it is already shown to produce suboptimal results. This paper proposes an ML-based method of model selection for cross-lingual transfer and shows consistently better results.