Zobrazeno 1 - 10
of 8 431
pro vyhledávání: '"Goethals A"'
Autor:
Goethals, Sofie, Rhue, Lauren
As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who the LLMs view as the most prominent figures across various fields,
Externí odkaz:
http://arxiv.org/abs/2412.10281
Time-resolved high-resolution X-ray Computed Tomography (4D $\mu$CT) is an imaging technique that offers insight into the evolution of dynamic processes inside materials that are opaque to visible light. Conventional tomographic reconstruction techni
Externí odkaz:
http://arxiv.org/abs/2412.00065
Autor:
Van Kenhove, Michiel, Seidler, Maximilian, Vandenberghe, Friedrich, Dujardin, Warre, Hennen, Wouter, Vogel, Arne, Sebrechts, Merlijn, Goethals, Tom, De Turck, Filip, Volckaert, Bruno
The rapid expansion of Internet of Things (IoT), edge, and embedded devices in the past decade has introduced numerous challenges in terms of security and configuration management. Simultaneously, advances in cloud-native development practices have g
Externí odkaz:
http://arxiv.org/abs/2410.22919
Access to resources strongly constrains the decisions we make. While we might wish to offer every student a scholarship, or schedule every patient for follow-up meetings with a specialist, limited resources mean that this is not possible. When deploy
Externí odkaz:
http://arxiv.org/abs/2406.01290
This study examines the use of Large Language Models (LLMs) for retrieving factual information, addressing concerns over their propensity to produce factually incorrect "hallucinated" responses or to altogether decline to even answer prompt at all. S
Externí odkaz:
http://arxiv.org/abs/2403.09148
Artificial Intelligence (AI) finds widespread application across various domains, but it sparks concerns about fairness in its deployment. The prevailing discourse in classification often emphasizes outcome-based metrics comparing sensitive subgroups
Externí odkaz:
http://arxiv.org/abs/2401.13391
Our online lives generate a wealth of behavioral records -'digital footprints'- which are stored and leveraged by technology platforms. This data can be used to create value for users by personalizing services. At the same time, however, it also pose
Externí odkaz:
http://arxiv.org/abs/2312.15000
Artificial Intelligence (AI) systems are increasingly used in high-stakes domains of our life, increasing the need to explain these decisions and to make sure that they are aligned with how we want the decision to be made. The field of Explainable AI
Externí odkaz:
http://arxiv.org/abs/2306.13885
In eXplainable Artificial Intelligence (XAI), counterfactual explanations are known to give simple, short, and comprehensible justifications for complex model decisions. However, we are yet to see more applied studies in which they are applied in rea
Externí odkaz:
http://arxiv.org/abs/2305.10069
Many organisations manage service quality and monitor a large set devices and servers where each entity is associated with telemetry or physical sensor data series. Recently, various methods have been proposed to detect behavioural anomalies, however
Externí odkaz:
http://arxiv.org/abs/2305.05538