Zobrazeno 1 - 10
of 40 225
pro vyhledávání: '"Mad, P"'
Autor:
Deniau, Laurent
The presentation will provide an overview of the capabilities of the Methodical Accelerator Design Next Generation (MAD-NG) tool. MAD-NG is a standalone, all-in-one, multi-platform tool well-suited for linear and nonlinear optics design and optimizat
Externí odkaz:
http://arxiv.org/abs/2412.16006
Autor:
Lakara, Kumud, Sock, Juil, Rupprecht, Christian, Torr, Philip, Collomosse, John, de Witt, Christian Schroeder
One of the most challenging forms of misinformation involves the out-of-context (OOC) use of images paired with misleading text, creating false narratives. Existing AI-driven detection systems lack explainability and require expensive fine-tuning. We
Externí odkaz:
http://arxiv.org/abs/2410.20140
Autor:
Chen, Eason, Tang, Xinyi, Xiao, Zimo, Li, Chuangji, Li, Shizhuo, Tingguan, Wu, Wang, Siyun, Chalkias, Kostas Kryptos
Web3 aims to enhance user control over data and assets, but this vision is challenged by non-transparent, scam-prone applications and vulnerable smart contracts. While code audits are one solution to this problem, the lack of smart contracts source c
Externí odkaz:
http://arxiv.org/abs/2410.15275
Autor:
Voelcker, Claas A, Hussing, Marcel, Eaton, Eric, Farahmand, Amir-massoud, Gilitschenski, Igor
Building deep reinforcement learning (RL) agents that find a good policy with few samples has proven notoriously challenging. To achieve sample efficiency, recent work has explored updating neural networks with large numbers of gradient steps for eve
Externí odkaz:
http://arxiv.org/abs/2410.08896
Autor:
Wüst, Antonia, Tobiasch, Tim, Helff, Lukas, Dhami, Devendra S., Rothkopf, Constantin A., Kersting, Kristian
Recently, newly developed Vision-Language Models (VLMs), such as OpenAI's GPT-4o, have emerged, seemingly demonstrating advanced reasoning capabilities across text and image modalities. Yet, the depth of these advances in language-guided perception a
Externí odkaz:
http://arxiv.org/abs/2410.19546
Autor:
Kang, Mingu, Lee, Dongseok, Cho, Woojin, Park, Jaehyeon, Lee, Kookjin, Gruber, Anthony, Hong, Youngjoon, Park, Noseong
Large language models (LLMs), like ChatGPT, have shown that even trained with noisy prior data, they can generalize effectively to new tasks through in-context learning (ICL) and pre-training techniques. Motivated by this, we explore whether a simila
Externí odkaz:
http://arxiv.org/abs/2410.06442
Based on the magnetization, an accretion disk with large-scale magnetic field can be separated into either standard and normal evolution (SANE) or magnetically arrested disk (MAD), which are difficult to identify from observations. It is still unclea
Externí odkaz:
http://arxiv.org/abs/2408.00321
In our study, we examine a 2D radiation, relativistic, magnetohydrodynamics (Rad-RMHD) accretion flows around a spinning supermassive black hole. We begin by setting an initial equilibrium torus around the black hole, with an embedded initial magneti
Externí odkaz:
http://arxiv.org/abs/2406.10496
Autor:
Futeral, Matthieu, Agostinelli, Andrea, Tagliasacchi, Marco, Zeghidour, Neil, Kharitonov, Eugene
Generative spoken language models produce speech in a wide range of voices, prosody, and recording conditions, seemingly approaching the diversity of natural speech. However, the extent to which generated speech is acoustically diverse remains unclea
Externí odkaz:
http://arxiv.org/abs/2404.10419
In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-world operational scenarios. While current morphing attack detection metho
Externí odkaz:
http://arxiv.org/abs/2404.06963