Zobrazeno 1 - 10
of 201
pro vyhledávání: '"Merialdo, P."'
Autor:
Verdini, Francesco, Melucci, Pierfrancesco, Perna, Stefano, Cariaggi, Francesco, Gaido, Marco, Papi, Sara, Mazurek, Szymon, Kasztelnik, Marek, Bentivogli, Luisa, Bratières, Sébastien, Merialdo, Paolo, Scardapane, Simone
The remarkable performance achieved by Large Language Models (LLM) has driven research efforts to leverage them for a wide range of tasks and input modalities. In speech-to-text (S2T) tasks, the emerging solution consists of projecting the output of
Externí odkaz:
http://arxiv.org/abs/2409.17044
Autor:
Teofili, Tommaso, Firmani, Donatella, Koudas, Nick, Martello, Vincenzo, Merialdo, Paolo, Srivastava, Divesh
Entity resolution (ER) aims at matching records that refer to the same real-world entity. Although widely studied for the last 50 years, ER still represents a challenging data management problem, and several recent works have started to investigate t
Externí odkaz:
http://arxiv.org/abs/2203.12978
Autor:
Crescenzi, Valter, De Angelis, Andrea, Firmani, Donatella, Mazzei, Maurizio, Merialdo, Paolo, Piai, Federico, Srivastava, Divesh
Data integration is a long-standing interest of the data management community and has many disparate applications, including business, science and government. We have recently witnessed impressive results in specific data integration tasks, such as E
Externí odkaz:
http://arxiv.org/abs/2101.11259
Knowledge Graphs (KGs) have found many applications in industry and academic settings, which in turn, have motivated considerable research efforts towards large-scale information extraction from a variety of sources. Despite such efforts, it is well
Externí odkaz:
http://arxiv.org/abs/2002.00819
The design of activation functions is a growing research area in the field of neural networks. In particular, instead of using fixed point-wise functions (e.g., the rectified linear unit), several authors have proposed ways of learning these function
Externí odkaz:
http://arxiv.org/abs/1901.10232
Autor:
Grönroos, Stig-Arne, Huet, Benoit, Kurimo, Mikko, Laaksonen, Jorma, Merialdo, Bernard, Pham, Phu, Sjöberg, Mats, Sulubacak, Umut, Tiedemann, Jörg, Troncy, Raphael, Vázquez, Raúl
This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation Shared Task. We propose adapting the Transformer neural machine translation (NMT) architecture to a multi-modal setting. In this paper, we also describe the prelim
Externí odkaz:
http://arxiv.org/abs/1808.10802
In Codice Ratio is a research project to study tools and techniques for analyzing the contents of historical documents conserved in the Vatican Secret Archives (VSA). In this paper, we present our efforts to develop a system to support the transcript
Externí odkaz:
http://arxiv.org/abs/1803.03200
Autor:
Lange, Mona, Kott, Alexander, Ben-Asher, Noam, Mees, Wim, Baykal, Nazife, Vidu, Cristian-Mihai, Merialdo, Matteo, Malowidzki, Marek, Madahar, Bhopinder
The North Atlantic Treaty Organization (NATO) Exploratory Team meeting, "Model-Driven Paradigms for Integrated Approaches to Cyber Defense," was organized by the NATO Science and Technology Organization's (STO) Information Systems and Technology (IST
Externí odkaz:
http://arxiv.org/abs/1703.03306
In this paper, we present a meta-analysis of several Web content extraction algorithms, and make recommendations for the future of content extraction on the Web. First, we find that nearly all Web content extractors do not consider a very large, and
Externí odkaz:
http://arxiv.org/abs/1508.04066