Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Pavel Přibáň"'
Publikováno v:
Proceedings of the 15th International Conference on Agents and Artificial Intelligence.
Autor:
Pavel Přibáň, Alexandra Balahur
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243394
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8359dac23acf2810057d40f857aa21e1
https://doi.org/10.1007/978-3-031-24340-0_20
https://doi.org/10.1007/978-3-031-24340-0_20
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783031162695
This paper deals with cross-lingual sentiment analysis in Czech, English and French languages. We perform zero-shot cross-lingual classification using five linear transformations combined with LSTM and CNN based classifiers. We compare the performanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17b7bdf8cf76948be91377b4e3b159cf
http://arxiv.org/abs/2209.07244
http://arxiv.org/abs/2209.07244
Autor:
Pavel Přibáň, Steinberger, Josef
Publikováno v:
Web of Science
In this paper, we introduce a new Czech subjectivity dataset of 10k manually annotated subjective and objective sentences from movie reviews and descriptions. Our prime motivation is to provide a reliable dataset that can be used with the existing En
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::539e4e0ff28497f30be348e8f1f7d1df
http://arxiv.org/abs/2204.13915
http://arxiv.org/abs/2204.13915
Publikováno v:
RANLP
This paper describes the training process of the first Czech monolingual language representation models based on BERT and ALBERT architectures. We pre-train our models on more than 340K of sentences, which is 50 times more than multilingual models th
Autor:
Josef Steinberger, Pavel Přibáň
Publikováno v:
RANLP
In this paper, we aim at improving Czech sentiment with transformer-based models and their multilingual versions. More concretely, we study the task of polarity detection for the Czech language on three sentiment polarity datasets. We fine-tune and p
Publikováno v:
SemEval@COLING
In this paper, we describe our method for the detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora, chosen from different time periods, for English, German, La
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d61b1fccf2f706b00d148b5d52351e24
http://arxiv.org/abs/2012.00004
http://arxiv.org/abs/2012.00004
Publikováno v:
RANLP
Detekce tzv. fake news a úzce souvisejícího ověřování faktů získala v poslední době velkou pozornost. Výzkum možností automatizace těchto úloh byl již částečně proveden v anglickém jazyce, ale pro ostatní jazyky existuje pouze
Autor:
Stephen Taylor, Pavel Přibáň
Publikováno v:
WANLP@ACL 2019
In this paper, we present our systems for the MADAR Shared Task: Arabic Fine-Grained Dialect Identification. The shared task consists of two subtasks. The goal of Subtask– 1 (S-1) is to detect an Arabic city dialect in a given text and the goal of
Autor:
Roman Yangarber, Lidia Pivovarova, Jakub Piskorski, Pavel Přibáň, Michał Marcińczuk, Josef Steinberger, Laska Laskova
Publikováno v:
BSNLP@ACL
University of Helsinki
University of Helsinki
We describe the Second Multilingual Named Entity Challenge in Slavic languages. The task is recognizing mentions of named entities in Web documents, their normalization, and cross-lingual linking The Challenge was organized as part of the 7th Balto-S