Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of large pretrained language models (LMs) to …

Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of a trained model to downstream natural language …

Contextualised word representation models have been successfully used for capturing
different word usages and they may be an attractive alternative for representing idiomaticity …

Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of large pretrained language models (LMs) to …

The process of protecting sensitive data is continually growing and becoming increasingly
important, especially as a result of the directives and laws imposed by the European Union …

The aim of this work is to develop efficient named entity recognition from the given text that in
turn improves the performance of the systems that use natural language processing (NLP) …

Accurate assessment of the ability of embedding models to capture idiomaticity may require
evaluation at token rather than type level, to account for degrees of idiomaticity and possible …

Modern approaches to Named Entity Recognition (NER) use neural networks (NN) to
automatically extract features from text and seamlessly integrate them with sequence …

Abstract Electronic Medical Records (EMRs) are written in an unstructured way, often using
natural language. Information Extraction (IE) may be used for acquiring knowledge from …

Having in mind that different languages might present different challenges, this paper
presents the following contributions to the area of Information Extraction from clinical text …