Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Garcia Silva, Andres"'
Detecting salient parts in text using natural language processing has been widely used to mitigate the effects of information overflow. Nevertheless, most of the datasets available for this task are derived mainly from academic publications. We intro
Externí odkaz:
http://arxiv.org/abs/2403.16941
Knowledge base population seeks to expand knowledge graphs with facts that are typically extracted from a text corpus. Recently, language models pretrained on large corpora have been shown to contain factual knowledge that can be retrieved using cloz
Externí odkaz:
http://arxiv.org/abs/2401.16293
Autor:
Gómez-Pérez, José Manuel, García-Silva, Andrés, Leone, Rosemarie, Albani, Mirko, Fontaine, Moritz, Poncet, Charles, Summerer, Leopold, Donati, Alessandro, Roma, Ilaria, Scaglioni, Stefano
The European Space Agency is well known as a powerful force for scientific discovery in numerous areas related to Space. The amount and depth of the knowledge produced throughout the different missions carried out by ESA and their contribution to sci
Externí odkaz:
http://arxiv.org/abs/2210.03640
Quality management and assurance is key for space agencies to guarantee the success of space missions, which are high-risk and extremely costly. In this paper, we present a system to generate quizzes, a common resource to evaluate the effectiveness o
Externí odkaz:
http://arxiv.org/abs/2210.03427
Autor:
García-Silva, Andrés, Berrío, Cristian, Gómez-Pérez, José Manuel, Martínez-Heras, José Antonio, Donati, Alessandro, Roma, Ilaria
We present SpaceQA, to the best of our knowledge the first open-domain QA system in Space mission design. SpaceQA is part of an initiative by the European Space Agency (ESA) to facilitate the access, sharing and reuse of information about Space missi
Externí odkaz:
http://arxiv.org/abs/2210.03422
In essence, embedding algorithms work by optimizing the distance between a word and its usual context in order to generate an embedding space that encodes the distributional representation of words. In addition to single words or word pieces, other f
Externí odkaz:
http://arxiv.org/abs/2104.06200
In this paper we shed light on the impact of fine-tuning over social media data in the internal representations of neural language models. We focus on bot detection in Twitter, a key task to mitigate and counteract the automatic spreading of disinfor
Externí odkaz:
http://arxiv.org/abs/2104.06182
We investigate the self-attention mechanism of BERT in a fine-tuning scenario for the classification of scientific articles over a taxonomy of research disciplines. We observe how self-attention focuses on words that are highly related to the domain
Externí odkaz:
http://arxiv.org/abs/2101.08114
Autor:
Garcia-Silva, Andres, Gomez-Perez, Jose Manuel, Palma, Raul, Krystek, Marcin, Mantovani, Simone, Foglini, Federica, Grande, Valentina, De Leo, Francesco, Salvi, Stefano, Trasati, Elisa, Romaniello, Vito, Albani, Mirko, Silvagni, Cristiano, Leone, Rosemarie, Marelli, Fulvio, Albani, Sergio, Lazzarini, Michele, Napier, Hazel J., Glaves, Helen M., Aldridge, Timothy, Meertens, Charles, Boler, Fran, Loescher, Henry W., Laney, Christine, Genazzio, Melissa A, Crawl, Daniel, Altintas, Ilkay
Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and reso
Externí odkaz:
http://arxiv.org/abs/1809.10617
Autor:
Garcia-Silva, Andres, Gomez-Perez, Jose Manuel, Palma, Raul, Krystek, Marcin, Mantovani, Simone, Foglini, Federica, Grande, Valentina, De Leo, Francesco, Salvi, Stefano, Trasatti, Elisa, Romaniello, Vito, Albani, Mirko, Silvagni, Cristiano, Leone, Rosemarie, Marelli, Fulvio, Albani, Sergio, Lazzarini, Michele, Napier, Hazel J., Glaves, Helen M., Aldridge, Timothy, Meertens, Charles, Boler, Fran, Loescher, Henry W., Laney, Christine, Genazzio, Melissa A., Crawl, Daniel, Altintas, Ilkay
Publikováno v:
In Future Generation Computer Systems September 2019 98:550-564
