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EMBEDDIA tools output example corpus of Estonian, Croatian and Latvian news articles 1.0
Freienthal, Linda; Pelicon, Andraž; Martinc, Matej. - : Ekspress Meedia Group, 2022. : Styria Media Group, 2022
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Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised? ...
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Word-embedding based bilingual terminology alignment ...
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Word-embedding based bilingual terminology alignment ...
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5
Ekspress news article archive (in Estonian and Russian) 1.0
Purver, Matthew; Pollak, Senja; Freienthal, Linda. - : Ekspress Meedia Group, 2021
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6
Latvian user comment dataset 1.0
Shekhar, Ravi; Purver, Matthew; Pollak, Senja. - : Ekspress Meedia Group, 2021
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7
Ekspress user comment dataset 1.0
Shekhar, Ravi; Pollak, Senja; Pelicon, Andraž. - : Ekspress Meedia Group, 2021
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8
24sata news comment dataset 1.0
Shekhar, Ravi; Pranjic, Marko; Pollak, Senja. - : Styria Media Group, 2021
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9
Keyword extraction datasets for Croatian, Estonian, Latvian and Russian 1.0
Koloski, Boshko; Pollak, Senja; Škrlj, Blaž. - : Ekspress Meedia Group, 2021. : Styria Media Group, 2021
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10
24sata news article archive 1.0
Purver, Matthew; Shekhar, Ravi; Pranjić, Marko. - : Styria Media Group, 2021
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11
Latvian Delfi article archive (in Latvian and Russian) 1.0
Pollak, Senja; Purver, Matthew; Shekhar, Ravi. - : Ekspress Meedia Group, 2021
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12
List of single-word male and female occupations in Slovenian
Supej, Anka; Ulčar, Matej; Robnik-Šikonja, Marko. - : Jožef Stefan Institute, 2021. : Faculty of Computer and Information Science, University of Ljubljana, 2021
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13
SimLex-999 Slovenian translation SimLex-999-sl 1.0
Pollak, Senja; Vulić, Ivan; Pelicon, Andraž. - : University of Ljubljana, 2021
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Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages ...
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Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages ...
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Evaluation of contextual embeddings on less-resourced languages ...
Abstract: The current dominance of deep neural networks in natural language processing is based on contextual embeddings such as ELMo, BERT, and BERT derivatives. Most existing work focuses on English; in contrast, we present here the first multilingual empirical comparison of two ELMo and several monolingual and multilingual BERT models using 14 tasks in nine languages. In monolingual settings, our analysis shows that monolingual BERT models generally dominate, with a few exceptions such as the dependency parsing task, where they are not competitive with ELMo models trained on large corpora. In cross-lingual settings, BERT models trained on only a few languages mostly do best, closely followed by massively multilingual BERT models. ... : 45 pages ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2107.10614
https://dx.doi.org/10.48550/arxiv.2107.10614
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17
Simple Discovery of COVID IS WAR Metaphors Using Word Embeddings ...
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Simple Discovery of COVID IS WAR Metaphors Using Word Embeddings ...
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19
Investigating cross-lingual training for offensive language detection
In: PeerJ Comput Sci (2021)
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20
Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech
In: Front Aging Neurosci (2021)
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