Zobrazeno 1 - 10
of 779
pro vyhledávání: '"Cherubin, P"'
Autor:
Debenedetti, Edoardo, Rando, Javier, Paleka, Daniel, Florin, Silaghi Fineas, Albastroiu, Dragos, Cohen, Niv, Lemberg, Yuval, Ghosh, Reshmi, Wen, Rui, Salem, Ahmed, Cherubin, Giovanni, Zanella-Beguelin, Santiago, Schmid, Robin, Klemm, Victor, Miki, Takahiro, Li, Chenhao, Kraft, Stefan, Fritz, Mario, Tramèr, Florian, Abdelnabi, Sahar, Schönherr, Lea
Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study this problem, we organized a capture-the-flag competition at IEEE SaT
Externí odkaz:
http://arxiv.org/abs/2406.07954
Autor:
Abdelnabi, Sahar, Fay, Aideen, Cherubin, Giovanni, Salem, Ahmed, Fritz, Mario, Paverd, Andrew
Large Language Models are commonly used in retrieval-augmented applications to execute user instructions based on data from external sources. For example, modern search engines use LLMs to answer queries based on relevant search results; email plugin
Externí odkaz:
http://arxiv.org/abs/2406.00799
Autor:
Cherubin, Giovanni, Köpf, Boris, Paverd, Andrew, Tople, Shruti, Wutschitz, Lukas, Zanella-Béguelin, Santiago
Machine learning models trained with differentially-private (DP) algorithms such as DP-SGD enjoy resilience against a wide range of privacy attacks. Although it is possible to derive bounds for some attacks based solely on an $(\varepsilon,\delta)$-D
Externí odkaz:
http://arxiv.org/abs/2402.14397
Multi-Level Intermediate Representation (MLIR) is gaining increasing attention in reconfigurable hardware communities due to its capability to represent various abstract levels for software compilers. This project aims to be the first to provide an e
Externí odkaz:
http://arxiv.org/abs/2401.10249
Autor:
Chukwudi Nwaogu, Bridget E. Diagi, Chinonye V. Ekweogu, Adedoyin Samuel Ajeyomi, Christopher C. Ejiogu, Enos I. Emereibeole, Patrick S. U. Eneche, Onyedikachi J. Okeke, David O. Edokpa, Enyinda Chike, Famous Ozabor, Obisesan Adekunle, Vremudia Onyeayana Wekpe, Osademe Chukwudi Dollah, Eshenake Ogaga, Hycienth O. Nwankwoala, Edwin Wallace, Chinedu Onugu, Temiloluwa Fajembola, Mauricio R. Cherubin
Publikováno v:
Discover Sustainability, Vol 5, Iss 1, Pp 1-24 (2024)
Abstract To address national and global demand for agro-based products, agricultural expansion has rapidly become a norm in Brazil since 1950s to date. In recent decades, agricultural expansion and technological advancement have placed the country am
Externí odkaz:
https://doaj.org/article/ff40326f13a749d2b8d9009f202a219b
Autor:
Rose Cherubin
Publikováno v:
Peitho, Vol 15, Iss 1 (2024)
Parmenides B 16/D51 presents an account of human cognition and understanding. It is usually taken to form part of the account of the untrustworthy opinions of mortals. Regardless of its proper location within the poem, it invokes difference, movement
Externí odkaz:
https://doaj.org/article/ae541df3048940e185c109827b7e3b85
Autor:
Matheus da Silva Araújo, Rafael Otto, José Lavres Junior, Vitor Corrêa de Mattos Barretto, Maurício Roberto Cherubin
Publikováno v:
Scientia Agricola, Vol 82 (2024)
ABSTRACT A bibliometric study was undertaken to analyze the spatiotemporal distribution of works related to managing boron (B) in Eucalyptus spp. from 1970 to 2022. This analysis was based on the Web of Science and Scopus databases, and 121 documents
Externí odkaz:
https://doaj.org/article/6fecaebd00f74c93b126698fc2cb7236
Autor:
Carlos Eduardo Pellegrino Cerri, Maurício Roberto Cherubin, João Marcos Villela, Jorge Luiz Locatelli, Martha Lustosa Carvalho, Federico Villarreal, Francisco Fujita de Castro Mello, Muhammad Akbar Ibrahim, Rattan Lal
Publikováno v:
Frontiers in Sustainable Food Systems, Vol 8 (2024)
Soil represents Earth’s largest terrestrial reservoir of carbon (C) and is an important sink of C from the atmosphere. However, the potential of adopting best management practices (BMPs) to increase soil C sequestration and offset greenhouse gas (G
Externí odkaz:
https://doaj.org/article/98a3a001f19846f2924ea4572faacd16
Autor:
Salem, Ahmed, Cherubin, Giovanni, Evans, David, Köpf, Boris, Paverd, Andrew, Suri, Anshuman, Tople, Shruti, Zanella-Béguelin, Santiago
Deploying machine learning models in production may allow adversaries to infer sensitive information about training data. There is a vast literature analyzing different types of inference risks, ranging from membership inference to reconstruction att
Externí odkaz:
http://arxiv.org/abs/2212.10986
Autor:
Fioravanti, Massimo, Cattaneo, Daniele, Terraneo, Federico, Seva, Silvano, Cherubin, Stefano, Agosta, Giovanni, Casella, Francesco, Leva, Alberto
Equation-based modelling is a powerful approach to tame the complexity of large-scale simulation problems. Equation-based tools automatically translate models into imperative languages. When confronted with nowadays' problems, however, well assessed
Externí odkaz:
http://arxiv.org/abs/2212.11135