Evaluating cross-lingual transfer: Interview with Dan Malkin

Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky received an honourable mention for contribution to methods at NAACL 2022 for their work A balanced data approach for evaluating cross-lingual transfer: mapping the linguistic blood bank. We spoke to Dan, who told us about multilingual models, the cross-lingual transfer phenomenon, and how the choice of pretraining languages affects downstream cross-lingual transfer. The topic of this research is multilingual models. Multilingual models are interesting because of the cross-lingual transfer phenomenon, in which a multilingual model pre-trained on many languages is able to transfer knowledge about a downstream particular task from one language to another. So, if you train a big model on various languages and then test it on a task, for example question-answering, in a different language, it can perform in a non-trivial manner.