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1	EMBEDDIA tools output example corpus of Estonian, Croatian and Latvian news articles 1.0
	Freienthal, Linda; Pelicon, Andraž; Martinc, Matej. - : Ekspress Meedia Group, 2022. : Styria Media Group, 2022
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2	Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised? ...
	Koloski, Boshko; Pollak, Senja; Škrlj, Blaž; Martinc, Matej. - : arXiv, 2022
	Abstract: Keyword extraction is the task of retrieving words that are essential to the content of a given document. Researchers proposed various approaches to tackle this problem. At the top-most level, approaches are divided into ones that require training - supervised and ones that do not - unsupervised. In this study, we are interested in settings, where for a language under investigation, no training data is available. More specifically, we explore whether pretrained multilingual language models can be employed for zero-shot cross-lingual keyword extraction on low-resource languages with limited or no available labeled training data and whether they outperform state-of-the-art unsupervised keyword extractors. The comparison is conducted on six news article datasets covering two high-resource languages, English and Russian, and four low-resource languages, Croatian, Estonian, Latvian, and Slovenian. We find that the pretrained models fine-tuned on a multilingual corpus covering languages that do not appear in the ...
	Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
	URL: https://arxiv.org/abs/2202.06650 https://dx.doi.org/10.48550/arxiv.2202.06650
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3	Keyword extraction datasets for Croatian, Estonian, Latvian and Russian 1.0
	Koloski, Boshko; Pollak, Senja; Škrlj, Blaž. - : Ekspress Meedia Group, 2021. : Styria Media Group, 2021
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