Zobrazeno 1 - 10
of 5 110
pro vyhledávání: '"A. Fornaciari"'
To defeat side-channel attacks, many recent countermeasures work by enforcing random run-time variability to the target computing platform in terms of clock jitters, frequency and voltage scaling, and phase shift, also combining the contributions fro
Externí odkaz:
http://arxiv.org/abs/2409.01881
This paper studies gender bias in machine translation through the lens of Large Language Models (LLMs). Four widely-used test sets are employed to benchmark various base LLMs, comparing their translation quality and gender bias against state-of-the-a
Externí odkaz:
http://arxiv.org/abs/2407.18786
Autor:
Gilabert, Javier García, Escolano, Carlos, Savall, Aleix Sant, Fornaciari, Francesca De Luca, Mash, Audrey, Liao, Xixian, Melero, Maite
In recent years, Large Language Models (LLMs) have demonstrated exceptional proficiency across a broad spectrum of Natural Language Processing (NLP) tasks, including Machine Translation. However, previous methods predominantly relied on iterative pro
Externí odkaz:
http://arxiv.org/abs/2406.09140
In this work, we explore idiomatic language processing with Large Language Models (LLMs). We introduce the Idiomatic language Test Suite IdioTS, a new dataset of difficult examples specifically designed by language experts to assess the capabilities
Externí odkaz:
http://arxiv.org/abs/2405.10579
Autor:
Leonardelli, Elisa, Uma, Alexandra, Abercrombie, Gavin, Almanea, Dina, Basile, Valerio, Fornaciari, Tommaso, Plank, Barbara, Rieser, Verena, Poesio, Massimo
NLP datasets annotated with human judgments are rife with disagreements between the judges. This is especially true for tasks depending on subjective judgments such as sentiment analysis or offensive language detection. Particularly in these latter c
Externí odkaz:
http://arxiv.org/abs/2304.14803
Detecting misinformation threads is crucial to guarantee a healthy environment on social media. We address the problem using the data set created during the COVID-19 pandemic. It contains cascades of tweets discussing information weakly labeled as re
Externí odkaz:
http://arxiv.org/abs/2304.02983
Autor:
Roberto Fanigliulo, Walter Stefanoni, Laura Fornaciari, Renato Grilli, Stefano Benigni, Daniela Scutaru, Giulio Sperandio, Daniele Pochi
Publikováno v:
AgriEngineering, Vol 6, Iss 2, Pp 1619-1638 (2024)
Wood fuel from the agroforestry sector is one of the main strategies cited by the EU for reducing energetic dependance on foreign markets. Its sustainability, both economic and environmental, can be improved through the optimization of harvesting and
Externí odkaz:
https://doaj.org/article/e07d8309f63440fd8b968d8c07130416
Publikováno v:
14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023)
NIST is conducting a process for the standardization of post-quantum cryptosystems, i.e., cryptosystems that are resistant to attacks by both traditional and quantum computers and that can thus substitute the traditional public-key cryptography solut
Externí odkaz:
http://arxiv.org/abs/2212.10636
The most common ways to explore latent document dimensions are topic models and clustering methods. However, topic models have several drawbacks: e.g., they require us to choose the number of latent dimensions a priori, and the results are stochastic
Externí odkaz:
http://arxiv.org/abs/2210.14763
Publikováno v:
Emergency Care Journal (2024)
Diabetic Ketoacidosis (DKA) is a potentially life-threatening condition that complicates diabetes mellitus. Euglycemic DKA (eDKA) is emerging as a variant in both type 1 and type 2 diabetes mellitus. The rise in its presentation is being caused by ne
Externí odkaz:
https://doaj.org/article/e455253d3bb24f78acef6d66f2872f51