49 citations · 69 across the 6 of their papers we have counts for
12 papers · 1 filter
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It
Lifeng Han, Gleb Erofeev, Irina Sorokina +2
Pre-trained language models (PLMs) often take advantage of the monolingual and multilingual dataset that is freely available online to acquire general or mixed domain knowledge bef…
Semantics Altering Modifications for Evaluating Comprehension in Machine Reading
Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro
Advances in NLP have yielded impressive results for the task of machine reading comprehension (MRC), with approaches having been reported to achieve performance comparable to that…
An efficient representation of chronological events in medical texts
Andrey Kormilitzin, Nemanja Vaci, Qiang Liu +3
In this work we addressed the problem of capturing sequential information contained in longitudinal electronic health records (EHRs). Clinical notes, which is a particular type of…
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models
Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro
Recent years have seen a growing number of publications that analyse Natural Language Inference (NLI) datasets for superficial cues, whether they undermine the complexity of the ta…
MASK: A flexible framework to facilitate de-identification of clinical texts
Nikola Milosevic, Gangamma Kalappa, Hesam Dadafarin +2
Medical health records and clinical summaries contain a vast amount of important information in textual form that can help advancing research on treatments, drugs and public health…
A Framework for Evaluation of Machine Reading Comprehension Gold Standards
Viktor Schlegel, Marco Valentino, André Freitas +2
Machine Reading Comprehension (MRC) is the task of answering a question over a paragraph of text. While neural MRC systems gain popularity and achieve noticeable performance, issue…