Zobrazeno 1 - 10
of 77 516
pro vyhledávání: '"A Selim"'
Path planning for wheeled mobile robots is a critical component in the field of automation and intelligent transportation systems. Car-like vehicles, which have non-holonomic constraints on their movement capability impose additional requirements on
Externí odkaz:
http://arxiv.org/abs/2411.18150
Alignment of pretrained LLMs using instruction-based datasets is critical for creating fine-tuned models that reflect human preference. A growing number of alignment-based fine-tuning algorithms and benchmarks emerged recently, fueling the efforts on
Externí odkaz:
http://arxiv.org/abs/2411.17792
Rapid identification of microparticles in liquid is an important problem in environmental and biomedical applications such as for microplastic detection in water sources and physiological fluids. Existing spectro-scopic techniques are usually slow an
Externí odkaz:
http://arxiv.org/abs/2411.12447
Autor:
Liu, Boya, Selim, Salem
We consider an inverse boundary value problem for the biharmonic operator with the first order perturbation in a bounded domain of dimension three or higher. Assuming that the first and the zeroth order perturbations are known in a neighborhood of th
Externí odkaz:
http://arxiv.org/abs/2411.07434
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