id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-020801-3sbicp3v	MacAvaney, Sean	Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-Shot Learning	2020-03-24		.txt	text/plain	2530	154	53	In this paper, we tackle the lack of data by leveraging pre-trained multilingual language models to transfer a retrieval system trained on English collections to non-English queries and documents. Our model is evaluated in a zero-shot setting, meaning that we use them to predict relevance scores for query-document pairs in languages never seen during training. [28] leveraged a data set of Wikipedia pages in 25 languages to train a learning to rank algorithm for Japanese-English and Swahili-English cross-language retrieval. In particular, to circumvent the lack of training data, we leverage transfer learning techniques to train Arabic, Mandarin, and Spanish retrieval models using English training data. We evaluate our models in a zero-shot setting; that is, we use them to predict relevance scores for query document pairs in languages never seen during training. Because large-scale relevance judgments are largely absent in languages other than English, we propose a new setting to evaluate learning-to-rank approaches: zero-shot cross-lingual ranking.	./cache/cord-020801-3sbicp3v.txt	./txt/cord-020801-3sbicp3v.txt