Zobrazeno 1 - 10
of 9 999
pro vyhledávání: '"Chunrong An"'
Autor:
Han, Tingxu, Sun, Weisong, Hu, Yanrong, Fang, Chunrong, Zhang, Yonglong, Ma, Shiqing, Zheng, Tao, Chen, Zhenyu, Wang, Zhenting
Text-to-image diffusion models have shown an impressive ability to generate high-quality images from input textual descriptions. However, concerns have been raised about the potential for these models to create content that infringes on copyrights or
Externí odkaz:
http://arxiv.org/abs/2412.00580
Redefining Crowdsourced Test Report Prioritization: An Innovative Approach with Large Language Model
Context: Crowdsourced testing has gained popularity in software testing, especially for mobile app testing, due to its ability to bring diversity and tackle fragmentation issues. However, the openness of crowdsourced testing presents challenges, part
Externí odkaz:
http://arxiv.org/abs/2411.17045
Under the notion of ergodicity of upper probability in the sense of Feng and Zhao (2021) that any invariant set either has capacity $0$ or its complement has capacity 0, we introduce the definition of finite ergodic components (FEC). We prove an inva
Externí odkaz:
http://arxiv.org/abs/2411.02030
We introduce the notion of common conditional expectation to investigate Birkhoff's ergodic theorem and subadditive ergodic theorem for invariant upper probabilities. If in addition, the upper probability is ergodic, we construct an invariant probabi
Externí odkaz:
http://arxiv.org/abs/2411.00663
Autor:
Chen, Yuchen, Sun, Weisong, Fang, Chunrong, Chen, Zhenpeng, Ge, Yifei, Han, Tingxu, Zhang, Quanjun, Liu, Yang, Chen, Zhenyu, Xu, Baowen
Language models for code (CodeLMs) have emerged as powerful tools for code-related tasks, outperforming traditional methods and standard machine learning approaches. However, these models are susceptible to security vulnerabilities, drawing increasin
Externí odkaz:
http://arxiv.org/abs/2410.15631
Autor:
Ge, Yifei, Sun, Weisong, Lou, Yihang, Fang, Chunrong, Zhang, Yiran, Li, Yiming, Zhang, Xiaofang, Liu, Yang, Zhao, Zhihong, Chen, Zhenyu
Recent advancements in large language models (LLMs) have revolutionized code intelligence by improving programming productivity and alleviating challenges faced by software developers. To further improve the performance of LLMs on specific code intel
Externí odkaz:
http://arxiv.org/abs/2410.02841
Software testing is a crucial phase in the software life cycle, helping identify potential risks and reduce maintenance costs. With the advancement of Large Language Models (LLMs), researchers have proposed an increasing number of LLM-based software
Externí odkaz:
http://arxiv.org/abs/2409.17561
In recent years, Deep Learning (DL) applications in JavaScript environment have become increasingly popular. As the infrastructure for DL applications, JavaScript DL frameworks play a crucial role in the development and deployment. It is essential to
Externí odkaz:
http://arxiv.org/abs/2409.14968
Regarding software engineering (SE) tasks, Large language models (LLMs) have the capability of zero-shot learning, which does not require training or fine-tuning, unlike pre-trained models (PTMs). However, LLMs are primarily designed for natural lang
Externí odkaz:
http://arxiv.org/abs/2409.14644
We study the small noise asymptotic for stochastic Burgers equations on $(0,1)$ with Dirichlet boundary condition. We consider the case that the noise is more singular than space-time white noise. We let the noise magnitude $\sqrt{\epsilon} \rightarr
Externí odkaz:
http://arxiv.org/abs/2409.14234