Zobrazeno 1 - 10
of 944
pro vyhledávání: '"Fornaciari, P. A."'
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:
Alberto Corriero, Anna Fornaciari, Samuel Terrazzino, Rossella Zangari, Antonio Izzi, Lorenzo Peluso, Marzia Savi, Chiara Faso, Laura Cavallini, Martina Polato, Eva Vitali, Sophie Schuind, Fabio Silvio Taccone, Elisa Gouvêa Bogossian
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
BackgroundApproximately one-third of trauma-related deaths are due to traumatic brain injury (TBI), particularly among young adults and elderly patients. Management strategies may vary across different age groups, potentially influencing short-term n
Externí odkaz:
https://doaj.org/article/08e961c9630b4740a02cbe4f8c893712
Autor:
Pierre Kateb, Alice Fornaciari, Chakaveh Ahmadizadeh, Alexander Shokurov, Fabio Cicoira, Carlo Menon
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 11, Pp n/a-n/a (2024)
Sensors based on everyday textiles are extremely promising for wearable applications. The present work focuses on high‐performance textile‐based capacitive strain sensors. Specifically, a conductive textile is obtained via vapor‐phase polymeriz
Externí odkaz:
https://doaj.org/article/71878b2cf1144c1a95a2ba451f704b37
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