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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Neural machine translation in academic contexts ... Delorme Benites, Alice; Benites, Fernando. - : ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2021 BASE Show details 2 University of Regensburg @ SwissText 2021 SEPP-NLG: Adding Sentence Structure to Unpunctuated Text Donabauer, Gregor; Kruschwitz, Udo. - : RWTH Aachen, 2021 Abstract: This paper describes our approach (UR- mSBD) to address the shared task on Sentence End and Punctuation Prediction in NLG Text (SEPP-NLG) organised as part of SwissText 2021. We participated in Subtask 1 (fully un- punctuated sentences – full stop detection) and submitted a run for every featured language (English, German, French, Italian). Our sub- missions are based on pre-trained BERT mod- els that have been fine-tuned to the task at hand. We had recently demonstrated, that such an ap- proach achieves state-of-the-art performance when identifying end-of-sentence markers on automatically transcribed texts. The difference to that work is that here we use language- specific BERT models for each featured lan- guage. By framing the problem as a binary tagging task using the outlined architecture we are able to achieve competitive results on the official test set across all languages, with Re- call, Precision, F1 ranging between 0.91 and 0.96 which makes us joint winners for Recall in two of the languages. The official baselines are beaten by large margins. Keyword: 020 Bibliotheks- und Informationswissenschaft; ddc:020 URL: https://epub.uni-regensburg.de/49352/1/sepp_paper5.pdf https://epub.uni-regensburg.de/49352/ http://ceur-ws.org/Vol-2957/ BASE Hide details 3 TwistBytes : hierarchical classification at GermEval 2019 : walking the fine line (of recall and precision) ... Benites, Fernando. - : German Society for Computational Linguistics & Language Technology, 2019 BASE Show details 4 The reader's feeling and text-based emotions : the relationship between subjective self-reports, lexical ratings, and sentiment analysis ... Werlen, Egon; Imhof, Christof; Benites, Fernando. - : CEUR Workshop Proceedings, 2019 BASE Show details 5 spMMMP at GermEval 2018 Shared Task: Classification of Offensive Content in Tweets using Convolutional Neural Networks and Gated Recurrent Units von Grünigen, Dirk; Benites, Fernando; Cieliebak, Mark... In: http://hw.oeaw.ac.at/8435-5 (2018) BASE Show details

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