Zobrazeno 11 - 20
of 17 340
pro vyhledávání: '"Fawaz AS"'
Autor:
Mangaokar, Neal, Hooda, Ashish, Choi, Jihye, Chandrashekaran, Shreyas, Fawaz, Kassem, Jha, Somesh, Prakash, Atul
Large language models (LLMs) are typically aligned to be harmless to humans. Unfortunately, recent work has shown that such models are susceptible to automated jailbreak attacks that induce them to generate harmful content. More recent LLMs often inc
Externí odkaz:
http://arxiv.org/abs/2402.15911
Autor:
Walendy, René, Weber, Markus, Li, Jingjie, Becker, Steffen, Wiesen, Carina, Elson, Malte, Kim, Younghyun, Fawaz, Kassem, Rummel, Nikol, Paar, Christof
Trust in digital systems depends on secure hardware, often assured through Hardware Reverse Engineering (HRE). This work develops methods for investigating human problem-solving processes in HRE, an underexplored yet critical aspect. Since reverse en
Externí odkaz:
http://arxiv.org/abs/2402.15452
Autor:
Hooda, Ashish, Christodorescu, Mihai, Allamanis, Miltiadis, Wilson, Aaron, Fawaz, Kassem, Jha, Somesh
Large Language Models' success on text generation has also made them better at code generation and coding tasks. While a lot of work has demonstrated their remarkable performance on tasks such as code completion and editing, it is still unclear as to
Externí odkaz:
http://arxiv.org/abs/2402.05980
Autor:
Ismail-Fawaz, Ali, Fawaz, Hassan Ismail, Petitjean, François, Devanne, Maxime, Weber, Jonathan, Berretti, Stefano, Webb, Geoffrey I., Forestier, Germain
Time series data can be found in almost every domain, ranging from the medical field to manufacturing and wireless communication. Generating realistic and useful exemplars and prototypes is a fundamental data analysis task. In this paper, we investig
Externí odkaz:
http://arxiv.org/abs/2309.16353
Autor:
Bacq-Labreuil, Benjamin, Fawaz, Chafic, Okazaki, Yuichi, Obata, Yukiko, Cercellier, Hervé, Lefevre, Patrick, Bertran, François, Santos-Cottin, David, Yamamoto, Hajime, Yamada, Ikuya, Azuma, Masaki, Horiba, Koji, Kumigashira, Hiroshi, d'Astuto, Matteo, Biermann, Silke, Lenz, Benjamin
We study two related universal anomalies of the spectral function of cuprates, so called waterfall and high-energy kink features, by a combined cellular dynamical mean-field theory and angle-resolved photoemission study for the oxychloride Na$_x$Ca$_
Externí odkaz:
http://arxiv.org/abs/2312.14381
Autor:
Fawaz, Hassan Ismail, Del Grosso, Ganesh, Kerdoncuff, Tanguy, Boisbunon, Aurelie, Saffar, Illyyne
Unsupervised Domain Adaptation (UDA) aims to harness labeled source data to train models for unlabeled target data. Despite extensive research in domains like computer vision and natural language processing, UDA remains underexplored for time series
Externí odkaz:
http://arxiv.org/abs/2312.09857
Over the past decade, Time Series Classification (TSC) has gained an increasing attention. While various methods were explored, deep learning - particularly through Convolutional Neural Networks (CNNs)-stands out as an effective approach. However, du
Externí odkaz:
http://arxiv.org/abs/2311.14534
This paper introduces GeoMorph, a novel geometric deep-learning framework designed for image registration of cortical surfaces. The registration process consists of two main steps. First, independent feature extraction is performed on each input surf
Externí odkaz:
http://arxiv.org/abs/2311.13022
Two grapes irradiated inside a microwave (MW) oven typically produce a series of sparks and can ignite a violent plasma. The underlying cause of the plasma has been attributed to the formation of morphological-dependent resonances (MDRs) in the aqueo
Externí odkaz:
http://arxiv.org/abs/2311.03951
This article demonstrates how variation of parameters can be successfully implemented in combination with other classical techniques, such as the method of characteristics, to derive novel classes of solutions to nonlinear partial differential equati
Externí odkaz:
http://arxiv.org/abs/2310.14082