Zobrazeno 1 - 10
of 194
pro vyhledávání: '"Saggion, Horacio"'
Autor:
Bott, Stefan, Saggion, Horacio, Rojas, Nelson Peréz, Salazar, Martin Solis, Ramirez, Saul Calderon
Automatic lexical simplification is a task to substitute lexical items that may be unfamiliar and difficult to understand with easier and more common words. This paper presents MultiLS-SP/CA, a novel dataset for lexical simplification in Spanish and
Externí odkaz:
http://arxiv.org/abs/2404.07814
Autor:
Perez-Rojas, Nelson, Calderon-Ramirez, Saul, Solis-Salazar, Martin, Romero-Sandoval, Mario, Arias-Monge, Monica, Saggion, Horacio
Text simplification, crucial in natural language processing, aims to make texts more comprehensible, particularly for specific groups like visually impaired Spanish speakers, a less-represented language in this field. In Spanish, there are few datase
Externí odkaz:
http://arxiv.org/abs/2312.09897
Patents are legal documents that aim at protecting inventions on the one hand and at making technical knowledge circulate on the other. Their complex style -- a mix of legal, technical, and extremely vague language -- makes their content hard to acce
Externí odkaz:
http://arxiv.org/abs/2310.15689
Autor:
Sheang, Kim Cheng, Saggion, Horacio
Text is by far the most ubiquitous source of knowledge and information and should be made easily accessible to as many people as possible; however, texts often contain complex words that hinder reading comprehension and accessibility. Therefore, sugg
Externí odkaz:
http://arxiv.org/abs/2307.02120
Text classification methods have been widely investigated as a way to detect content of low credibility: fake news, social media bots, propaganda, etc. Quite accurate models (likely based on deep neural networks) help in moderating public electronic
Externí odkaz:
http://arxiv.org/abs/2303.08032
Fine-tuning Transformer-based approaches have recently shown exciting results on sentence simplification task. However, so far, no research has applied similar approaches to the Lexical Simplification (LS) task. In this paper, we present ConLS, a Con
Externí odkaz:
http://arxiv.org/abs/2302.02900
Autor:
Saggion, Horacio, Štajner, Sanja, Ferrés, Daniel, Sheang, Kim Cheng, Shardlow, Matthew, North, Kai, Zampieri, Marcos
We report findings of the TSAR-2022 shared task on multilingual lexical simplification, organized as part of the Workshop on Text Simplification, Accessibility, and Readability TSAR-2022 held in conjunction with EMNLP 2022. The task called the Natura
Externí odkaz:
http://arxiv.org/abs/2302.02888
Autor:
Stajner, Sanja, Ferres, Daniel, Shardlow, Matthew, North, Kai, Zampieri, Marcos, Saggion, Horacio
Even in highly-developed countries, as many as 15-30\% of the population can only understand texts written using a basic vocabulary. Their understanding of everyday texts is limited, which prevents them from taking an active role in society and makin
Externí odkaz:
http://arxiv.org/abs/2209.05301
Autor:
Porcaro, Lorenzo, Saggion, Horacio
Recognizing Musical Entities is important for Music Information Retrieval (MIR) since it can improve the performance of several tasks such as music recommendation, genre classification or artist similarity. However, most entity recognition systems in
Externí odkaz:
http://arxiv.org/abs/1904.00648