Zobrazeno 1 - 10
of 1 796
pro vyhledávání: '"WANG Shaowei"'
Autor:
Sun, Zhi, Li, Tianyue, Kuang, Shiqi, Yun, Xue, He, Minru, Fu, Boyan, Fu, Yunlai, Zhao, Tianyu, Wang, Shaowei, Liang, Yansheng, Wang, Shuming, Lei, Ming
Metasurfaces are reshaping traditional optical paradigms and are increasingly required in complex applications that demand substantial computational resources to numerically solve Maxwell's equations-particularly for large-scale systems, inhomogeneou
Externí odkaz:
http://arxiv.org/abs/2412.08405
Autor:
Wang, Mengrui, Shu, Manming, Yan, Jiajing, Liu, Chang, Fu, Xiangda, Zhang, Jingxiang, Lin, Yuchen, Zhao, Hu, Huang, Yuwei, Ma, Dingbang, Ge, Yifan, Hao, Huiwen, Zhao, Tianyu, Liang, Yansheng, Wang, Shaowei, Lei, Ming
Three-dimensional (3D) fluorescence imaging provides a vital approach for study of biological tissues with intricate structures, and optical sectioning structured illumination microscopy (OS-SIM) stands out for its high imaging speed, low phototoxici
Externí odkaz:
http://arxiv.org/abs/2412.05677
Autor:
Zhang, Xinyu, Zhang, Lingling, Wu, Yanrui, Huang, Muye, Wu, Wenjun, Li, Bo, Wang, Shaowei, Liu, Jun
Visual Question Generation (VQG) has gained significant attention due to its potential in educational applications. However, VQG researches mainly focus on natural images, neglecting diagrams in educational materials used to assess students' conceptu
Externí odkaz:
http://arxiv.org/abs/2411.17771
Autor:
Dong, Ximing, Wang, Shaowei, Lin, Dayi, Rajbahadur, Gopi Krishnan, Zhou, Boquan, Liu, Shichao, Hassan, Ahmed E.
Large Language Models excel in tasks like natural language understanding and text generation. Prompt engineering plays a critical role in leveraging LLM effectively. However, LLMs black-box nature hinders its interpretability and effective prompting
Externí odkaz:
http://arxiv.org/abs/2410.13073
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge bases, achieving state-of-the-art results in various coding tasks. The core of RAG is retrieving demonstration examples, which is essential t
Externí odkaz:
http://arxiv.org/abs/2410.09662
Vulnerability fixes in open source software (OSS) usually follow the coordinated vulnerability disclosure model and are silently fixed. This delay can expose OSS users to risks as malicious parties might exploit the software before fixes are publicly
Externí odkaz:
http://arxiv.org/abs/2409.16606
Large language models (LLMs) like GitHub Copilot and ChatGPT have emerged as powerful tools for code generation, significantly enhancing productivity and accelerating software development. However, existing benchmarks primarily focus on general code
Externí odkaz:
http://arxiv.org/abs/2409.15228
Locating and fixing software faults is a time-consuming and resource-intensive task in software development. Traditional fault localization methods, such as Spectrum-Based Fault Localization (SBFL), rely on statistical analysis of test coverage data
Externí odkaz:
http://arxiv.org/abs/2409.13642
Imaginary Poynting momentum (IPM) provides a new degree of freedom for particle manipulation. However, the application of IPM in experiments has been largely unexplored. Here, we demonstrate the IPM driven particle rotation by cylindrically polarized
Externí odkaz:
http://arxiv.org/abs/2408.07301
Detecting vulnerabilities is vital for software security, yet deep learning-based vulnerability detectors (DLVD) face a data shortage, which limits their effectiveness. Data augmentation can potentially alleviate the data shortage, but augmenting vul
Externí odkaz:
http://arxiv.org/abs/2408.04125