Zobrazeno 1 - 10
of 77 341
pro vyhledávání: '"A, Selim"'
State-of-the-art RGB texture synthesis algorithms rely on style distances that are computed through statistics of deep features. These deep features are extracted by classification neural networks that have been trained on large datasets of RGB image
Externí odkaz:
http://arxiv.org/abs/2410.16019
Autor:
Nazar, Ahmad M., Celik, Abdulkadir, Selim, Mohamed Y., Abdallah, Asmaa, Qiao, Daji, Eltawil, Ahmed M.
Large language models (LLMs) hold significant promise in advancing network management and orchestration in 6G and beyond networks. However, existing LLMs are limited in domain-specific knowledge and their ability to handle multi-modal sensory data, w
Externí odkaz:
http://arxiv.org/abs/2410.18104
Combining large language models during training or at inference time has shown substantial performance gain over component LLMs. This paper presents LLM-TOPLA, a diversity-optimized LLM ensemble method with three unique properties: (i) We introduce t
Externí odkaz:
http://arxiv.org/abs/2410.03953
Autor:
Brandstetter, Sandra, Heintze, Carl, Subramanian, Keerthan, Hill, Paul, Preiss, Philipp M., Gałka, Maciej, Jochim, Selim
Understanding many body systems is a key challenge in physics. Single atom resolved imaging techniques have unlocked access to microscopic correlations in ultracold quantum gases. However they cannot be used when the relevant length scales are obscur
Externí odkaz:
http://arxiv.org/abs/2409.18954
Recent research demonstrates that the nascent fine-tuning-as-a-service business model exposes serious safety concerns -- fine-tuning over a few harmful data uploaded by the users can compromise the safety alignment of the model. The attack, known as
Externí odkaz:
http://arxiv.org/abs/2409.18169
Signal Processing (SP) and Machine Learning (ML) rely on good math and coding knowledge, in particular, linear algebra, probability, and complex numbers. A good grasp of these relies on scalar algebra learned in middle school. The ability to understa
Externí odkaz:
http://arxiv.org/abs/2409.17304
Autor:
Kartal, Enise, Selcuk, Yunus, Kaynak, Batuhan E., Yildiz, M. Taha, Yanik, Cenk, Hanay, M. Selim
Reservoir computing offers an energy-efficient alternative to deep neural networks (DNNs) by replacing complex hidden layers with a fixed nonlinear system and training only the final layer. This work investigates nanoelectromechanical system (NEMS) r
Externí odkaz:
http://arxiv.org/abs/2409.16805
This paper considers the minimization of a continuously differentiable function over a cardinality constraint. We focus on smooth and relatively smooth functions. These smoothness criteria result in new descent lemmas. Based on the new descent lemmas
Externí odkaz:
http://arxiv.org/abs/2409.12343
Autor:
Piozin, Corentin, Bouarroudj, Lisa, Audran, Jean-Yves, Lavrard, Brice, Simon, Catherine, Waszak, Florian, Eskiizmirliler, Selim
Decoding multiple movements from the same limb using electroencephalographic (EEG) activity is a key challenge with applications for controlling prostheses in upper-limb amputees. This study investigates the classification of four hand movements to c
Externí odkaz:
http://arxiv.org/abs/2409.07207
Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation
Harmful fine-tuning issue \citep{qi2023fine} poses serious safety concerns for Large language models' fine-tuning-as-a-service. While existing defenses \citep{huang2024vaccine,rosati2024representation} have been proposed to mitigate the issue, their
Externí odkaz:
http://arxiv.org/abs/2409.01586