Zobrazeno 1 - 10
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pro vyhledávání: '"Wang, Yanlin"'
Autor:
Chen, Jiachi, Zhong, Qingyuan, Wang, Yanlin, Ning, Kaiwen, Liu, Yongkun, Xu, Zenan, Zhao, Zhe, Chen, Ting, Zheng, Zibin
The emergence of Large Language Models (LLMs) has significantly influenced various aspects of software development activities. Despite their benefits, LLMs also pose notable risks, including the potential to generate harmful content and being abused
Externí odkaz:
http://arxiv.org/abs/2409.15154
Autor:
Wang, Yanlin, Zhong, Wanjun, Huang, Yanxian, Shi, Ensheng, Yang, Min, Chen, Jiachi, Li, Hui, Ma, Yuchi, Wang, Qianxiang, Zheng, Zibin
In recent years, Large Language Models (LLMs) have achieved remarkable success and have been widely used in various downstream tasks, especially in the tasks of the software engineering (SE) field. We find that many studies combining LLMs with SE hav
Externí odkaz:
http://arxiv.org/abs/2409.09030
Autor:
Yang, Shuo, Lin, Xingwei, Chen, Jiachi, Zhong, Qingyuan, Xiao, Lei, Huang, Renke, Wang, Yanlin, Zheng, Zibin
The rapid advancement of blockchain platforms has significantly accelerated the growth of decentralized applications (DApps). Similar to traditional applications, DApps integrate front-end descriptions that showcase their features to attract users, a
Externí odkaz:
http://arxiv.org/abs/2408.06037
Autor:
Wang, Yanlin, Guo, Lianghong, Shi, Ensheng, Chen, Wenqing, Chen, Jiachi, Zhong, Wanjun, Wang, Menghan, Li, Hui, Zhang, Hongyu, Lyu, Ziyu, Zheng, Zibin
Code search plays a crucial role in software development, enabling developers to retrieve and reuse code using natural language queries. While the performance of code search models improves with an increase in high-quality data, obtaining such data c
Externí odkaz:
http://arxiv.org/abs/2408.05542
Autor:
Zhang, Jiashuo, Shen, Yiming, Chen, Jiachi, Su, Jianzhong, Wang, Yanlin, Chen, Ting, Gao, Jianbo, Chen, Zhong
Ethereum has officially provided a set of system-level cryptographic APIs to enhance smart contracts with cryptographic capabilities. These APIs have been utilized in over 10% of Ethereum transactions, motivating developers to implement various on-ch
Externí odkaz:
http://arxiv.org/abs/2408.04939
Graph learning methods have been extensively applied in diverse application areas. However, what kind of inherent graph properties e.g. graph proximity, graph structural information has been encoded into graph representation learning for downstream t
Externí odkaz:
http://arxiv.org/abs/2408.03877
Autor:
Ning, Kaiwen, Chen, Jiachi, Zhong, Qingyuan, Zhang, Tao, Wang, Yanlin, Li, Wei, Zhang, Yu, Zhang, Weizhe, Zheng, Zibin
With the advent of large language models (LLMs), numerous software service providers (SSPs) are dedicated to developing LLMs customized for code generation tasks, such as CodeLlama and Copilot. However, these LLMs can be leveraged by attackers to cre
Externí odkaz:
http://arxiv.org/abs/2408.01354
Autor:
Guo, Lianghong, Wang, Yanlin, Shi, Ensheng, Zhong, Wanjun, Zhang, Hongyu, Chen, Jiachi, Zhang, Ruikai, Ma, Yuchi, Zheng, Zibin
Code generation aims to automatically generate code snippets that meet given natural language requirements and plays an important role in software development. Although Code LLMs have shown excellent performance in this domain, their long generation
Externí odkaz:
http://arxiv.org/abs/2407.20042
Publikováno v:
47th International Conference on Software Engineering (ICSE 2025)
Repository-level code completion aims to generate code for unfinished code snippets within the context of a specified repository. Existing approaches mainly rely on retrieval-augmented generation strategies due to limitations in input sequence length
Externí odkaz:
http://arxiv.org/abs/2407.19487
Smart contract developers frequently seek solutions to developmental challenges on Q&A platforms such as Stack Overflow (SO). Although community responses often provide viable solutions, the embedded code snippets can also contain hidden vulnerabilit
Externí odkaz:
http://arxiv.org/abs/2407.13271