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pro vyhledávání: '"An, Qiang"'
The field of medical image segmentation is challenged by domain generalization (DG) due to domain shifts in clinical datasets. The DG challenge is exacerbated by the scarcity of medical data and privacy concerns. Traditional single-source domain gene
Externí odkaz:
http://arxiv.org/abs/2409.04768
The DArk Matter Particle Explorer (DAMPE) is a satellite-borne particle detector for measurements of high-energy cosmic rays and {\gamma}-rays. DAMPE has been operating smoothly in space for more than 8 years since launch on December 17, 2015. The tr
Externí odkaz:
http://arxiv.org/abs/2409.03352
The significant increase in software production driven by automation and faster development lifecycles has resulted in a corresponding surge in software vulnerabilities. In parallel, the evolving landscape of software vulnerability detection, highlig
Externí odkaz:
http://arxiv.org/abs/2408.16400
Autor:
Liu, Zihan, Zeng, Ruinan, Wang, Dongxia, Peng, Gengyun, Wang, Jingyi, Liu, Qiang, Liu, Peiyu, Wang, Wenhai
In industrial control systems, the generation and verification of Programmable Logic Controller (PLC) code are critical for ensuring operational efficiency and safety. While Large Language Models (LLMs) have made strides in automated code generation,
Externí odkaz:
http://arxiv.org/abs/2410.14209
Publikováno v:
The European Physical Journal C 84,1075 (2024)
We examine the accretion process in a thin disk surrounding a supermassive black hole within the framework of Einstein-Maxwell-scalar (EMS) gravity. Our investigation aims to elucidate how variations in model parameters affect different physical prop
Externí odkaz:
http://arxiv.org/abs/2410.14113
Deep learning models have made remarkable strides in precipitation prediction, yet they continue to struggle with capturing the spatial details of the features of radar images, particularly over high precipitation intensity areas. This shortcoming is
Externí odkaz:
http://arxiv.org/abs/2410.14103
Autor:
Sun, Yanpeng, Zhang, Huaxin, Chen, Qiang, Zhang, Xinyu, Sang, Nong, Zhang, Gang, Wang, Jingdong, Li, Zechao
We focus on improving the visual understanding capability for boosting the vision-language models. We propose \textbf{Arcana}, a multiModal language model, which introduces two crucial techniques. First, we present Multimodal LoRA (MM-LoRA), a module
Externí odkaz:
http://arxiv.org/abs/2410.13733
Autor:
Tang, Jau, Tang, Qiang
We modify the Yang-Mills model using massless preon pairs to describe the photon isospin singlet and the Z and W bosons. Unlike the Higgs mechanism, which depends on a scalar field, our model employs Gell-Mann generators, revealing that the masses of
Externí odkaz:
http://arxiv.org/abs/2410.13902
We investigate strong gravitational lensing by two static black hole models (Model-1 and Model-2) within the Effective Quantum Gravity (EQG) framework, characterized by mass $M$ and parameter $\zeta$. For $\zeta = 0$, they reduce to the Schwarzschild
Externí odkaz:
http://arxiv.org/abs/2410.12382
Most knowledge distillation (KD) methodologies predominantly focus on teacher-student pairs with similar architectures, such as both being convolutional neural networks (CNNs). However, the potential and flexibility of KD can be greatly improved by e
Externí odkaz:
http://arxiv.org/abs/2410.12342