The transformer-based pre-trained language model BERT has helped to improve state-of-
the-art performance on many natural language processing (NLP) tasks. Using the same …

The aim of this contribution is to reflect on the process of building the multilingual European
Literary Text Collection (ELTeC) that is being created in the framework of the networking …

This paper presents the ParlaMint corpora containing transcriptions of the sessions of the 17
European national parliaments with half a billion words. The corpora are uniformly encoded …

We present UDify, a multilingual multi-task model capable of accurately predicting universal
part-of-speech, morphological features, lemmas, and dependency trees simultaneously for …

Natural language processing (NLP) systems have become a central technology in
communication, education, medicine, artificial intelligence, and many other domains of …

Ancient languages preserve the cultures and histories of the past. However, their study is
fraught with difficulties, and experts must tackle a range of challenging text-based tasks, from …

While the problem of vaccine hesitancy is not new, it has become more pronounced with the
new COVID-19 vaccines and represents an obstacle to resolving the crisis. Even people …

Recent advances in multilingual dependency parsing have brought the idea of a truly
universal parser closer to reality. However, cross-language interference and restrained …

We present RobeCzech, a monolingual RoBERTa language representation model trained
on Czech data. RoBERTa is a robustly optimized Transformer-based pretraining approach …

Transfer learning, particularly approaches that combine multi-task learning with pre-trained
contextualized embeddings and fine-tuning, have advanced the field of Natural Language …