no code implementations • EAMT 2022 • Tamás Váradi, Marko Tadić, Svetla Koeva, Maciej Ogrodniczuk, Dan Tufiş, Radovan Garabík, Simon Krek, Andraž Repar
The work in progress on the CEF Action CURLICA T is presented.
no code implementations • EACL (Hackashop) 2021 • Andraž Repar, Andrej Shumakov
This paper presents the implementation of a bilingual term alignment approach developed by Repar et al. (2019) to a dataset of unaligned Estonian and Russian keywords which were manually assigned by journalists to describe the article topic.
no code implementations • LREC 2022 • Tamás Váradi, Bence Nyéki, Svetla Koeva, Marko Tadić, Vanja Štefanec, Maciej Ogrodniczuk, Bartłomiej Nitoń, Piotr Pęzik, Verginica Barbu Mititelu, Elena Irimia, Maria Mitrofan, Dan Tufiș, Radovan Garabík, Simon Krek, Andraž Repar
This article presents the current outcomes of the CURLICAT CEF Telecom project, which aims to collect and deeply annotate a set of large corpora from selected domains.
no code implementations • 22 Jul 2021 • Matej Ulčar, Aleš Žagar, Carlos S. Armendariz, Andraž Repar, Senja Pollak, Matthew Purver, Marko Robnik-Šikonja
The current dominance of deep neural networks in natural language processing is based on contextual embeddings such as ELMo, BERT, and BERT derivatives.
1 code implementation • 15 Jul 2019 • Blaž Škrlj, Andraž Repar, Senja Pollak
Keyword extraction is used for summarizing the content of a document and supports efficient document retrieval, and is as such an indispensable part of modern text-based systems.