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pro vyhledávání: '"Backes AN"'
LiV$_2$O$_4$ is a member of the so-called $3d$ heavy fermion compounds, with effective electron mass exceeding 60 times the free electron mass, comparable to $4f$ heavy fermion compounds. The origin of the strong electron correlation in combination w
Externí odkaz:
http://arxiv.org/abs/2410.08515
Human Pose Estimation (HPE) has been widely applied in autonomous systems such as self-driving cars. However, the potential risks of HPE to adversarial attacks have not received comparable attention with image classification or segmentation tasks. Ex
Externí odkaz:
http://arxiv.org/abs/2410.07670
Autor:
Goldoni, P., Boisson, C., Pita, S., D'Ammando, F., Kasai, E., Max-Moerbeck, W., Backes, M., Cotter, G.
Context: PKS 0903-57 is a little-studied gamma-ray blazar which has recently attracted considerable interest due to the strong flaring episodes observed since 2020 in HE (100 MeV < E < 100 GeV) and VHE (100 GeV < E < 10 TeV) gamma-rays. Its nature an
Externí odkaz:
http://arxiv.org/abs/2410.06744
Large vision-language models (LVLMs) have been rapidly developed and widely used in various fields, but the (potential) stereotypical bias in the model is largely unexplored. In this study, we present a pioneering measurement framework, $\texttt{ModS
Externí odkaz:
http://arxiv.org/abs/2410.06967
Recent work on studying memorization in self-supervised learning (SSL) suggests that even though SSL encoders are trained on millions of images, they still memorize individual data points. While effort has been put into characterizing the memorized d
Externí odkaz:
http://arxiv.org/abs/2409.19069
Large language models (LLMs) have shown considerable success in a range of domain-specific tasks, especially after fine-tuning. However, fine-tuning with real-world data usually leads to privacy risks, particularly when the fine-tuning samples exist
Externí odkaz:
http://arxiv.org/abs/2409.11423
Machine learning has revolutionized numerous domains, playing a crucial role in driving advancements and enabling data-centric processes. The significance of data in training models and shaping their performance cannot be overstated. Recent research
Externí odkaz:
http://arxiv.org/abs/2409.03741
Adapting Large Language Models (LLMs) to specific tasks introduces concerns about computational efficiency, prompting an exploration of efficient methods such as In-Context Learning (ICL). However, the vulnerability of ICL to privacy attacks under re
Externí odkaz:
http://arxiv.org/abs/2409.01380
Text-to-image models, such as Stable Diffusion (SD), undergo iterative updates to improve image quality and address concerns such as safety. Improvements in image quality are straightforward to assess. However, how model updates resolve existing conc
Externí odkaz:
http://arxiv.org/abs/2408.17285
Autor:
Nilsson, K., Ramazani, V. Fallah, Lindfors, E., Goldoni, P., González, J. Becerra, Pulido, J. A. Acosta, Clavero, R., Otero-Santos, J., Pursimo, T., Pita, S., Kouch, P. M., Boisson, C., Backes, M., Cotter, G., D'Ammando, F., Kasai, E.
Direct redshift determination of BL Lac objects is highly challenging as the emission in the optical and near-infrared (NIR) bands is largely dominated by the non-thermal emission from the relativistic jet that points very close to our line of sight.
Externí odkaz:
http://arxiv.org/abs/2408.14854