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pro vyhledávání: '"Lambert Mathias"'
Akademický článek
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Akademický článek
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Autor:
Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Lambert Mathias, Marzieh Saeidi, Veselin Stoyanov, Majid Yazdani
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Autor:
Caselli, Tommaso, Schelhaas, Arjan, Weultjes, Marieke, Leistra, Folkert, van der Veen, Hylke, Timmerman, Gerben, Nissim, Malvina, Mostafazadeh Davani, Aida, Kiela, Douwe, Lambert, Mathias, Vidgen, Bertie, Prabhakaran, Vinodkumar, Waseem, Zeerak
Publikováno v:
Proceedings of the 5th Workshop on Online Abuse and Harm, 54-66
STARTPAGE=54;ENDPAGE=66;TITLE=Proceedings of the 5th Workshop on Online Abuse and Harm
STARTPAGE=54;ENDPAGE=66;TITLE=Proceedings of the 5th Workshop on Online Abuse and Harm
As socially unacceptable language become pervasive in social media platforms, the need for automatic content moderation become more pressing. This contribution introduces the Dutch Abusive Language Corpus (DALC v1.0), a new dataset with tweets manual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1381a0890cf72aacf90bfcb3f2f47c32
https://doi.org/10.18653/v1/2021.woah-1.6
https://doi.org/10.18653/v1/2021.woah-1.6
Autor:
Caselli, Tommaso, Basile, Valerio, Mitrović, Jelena, Granitzer, Michael, Mostafazadeh Davani, Aida, Kiela, Douwe, Lambert, Mathias, Vidgen, Bertie, Prabhakaran, Vinodkumar, Waseem, Zeerak
Publikováno v:
Proceedings of the 5th Workshop on Online Abuse and Harm, 17-25
STARTPAGE=17;ENDPAGE=25;TITLE=Proceedings of the 5th Workshop on Online Abuse and Harm
STARTPAGE=17;ENDPAGE=25;TITLE=Proceedings of the 5th Workshop on Online Abuse and Harm
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in English. The model was trained on RAL-E, a large-scale dataset of Reddit comments in English from communities banned for being offensive, abusive, or hate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f26463d8da1e9828b720686dc2eb86ae
https://doi.org/10.18653/v1/2021.woah-1.3
https://doi.org/10.18653/v1/2021.woah-1.3
Akademický článek
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Autor:
Aida Mostafazadeh Davani, Vinodkumar Prabhakaran, Bertie Vidgen, Shaoliang Nie, Douwe Kiela, Lambert Mathias, Zeerak Waseem
Publikováno v:
Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021).
We present the results and main findings of the shared task at WOAH 5 on hateful memes detection. The task include two subtasks relating to distinct challenges in the fine-grained detection of hateful memes: (1) the protected category attacked by the
Autor:
Milovic, Carlos, Lambert, Mathias, Langkammer, Christian, Bredies, Kristian, Irarrazaval, Pablo, Tejos, Cristian
Publikováno v:
Magnetic Resonance in Medicine; Jan2022, Vol. 87 Issue 1, p457-473, 17p
Autor:
Lambert Mathias, Rylan Conway
Publikováno v:
SIGdial
In a spoken dialogue system, dialogue state tracker (DST) components track the state of the conversation by updating a distribution of values associated with each of the slots being tracked for the current user turn, using the interactions until then
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7eaf1734b76fbed7946ce4673391c8a0
http://arxiv.org/abs/1907.11315
http://arxiv.org/abs/1907.11315
Tracking the state of the conversation is a central component in task-oriented spoken dialogue systems. One such approach for tracking the dialogue state is slot carryover, where a model makes a binary decision if a slot from the context is relevant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed712b000f18567165d1bf078bfc9c25
http://arxiv.org/abs/1906.01149
http://arxiv.org/abs/1906.01149