Zobrazeno 1 - 10
of 1 058
pro vyhledávání: '"An, Xiangzhe"'
Recent advances in code-specific large language models (LLMs) have greatly enhanced code generation and refinement capabilities. However, the safety of code LLMs remains under-explored, posing potential risks as insecure code generated by these model
Externí odkaz:
http://arxiv.org/abs/2411.12882
Autor:
Hu, Siying, Yuan, Xiangzhe, Wang, Jiajun, Wang, Piaohong, Ma, Jian, Wu, Zhiyang, Wan, Qian, Lu, Zhicong
Sports highlights are becoming increasingly popular on video-sharing platforms. Yet, crafting sport highlight videos is challenging, which requires producing engaging narratives from different angles, and conforming to different platform affordances
Externí odkaz:
http://arxiv.org/abs/2409.13443
With the development of generative AI technology, a vast array of AI-generated paintings (AIGP) have gone viral on social media like TikTok. However, some negative news about AIGP has also emerged. For example, in 2022, numerous painters worldwide or
Externí odkaz:
http://arxiv.org/abs/2409.11911
As the demand for computer science (CS) skills grows, mastering foundational concepts is crucial yet challenging for novice learners. To address this challenge, we present KoroT-3E, an AI-based system that creates personalized musical mnemonics to en
Externí odkaz:
http://arxiv.org/abs/2409.10446
Autor:
Feng, Shiwei, Ye, Yapeng, Shi, Qingkai, Cheng, Zhiyuan, Xu, Xiangzhe, Cheng, Siyuan, Choi, Hongjun, Zhang, Xiangyu
As Autonomous driving systems (ADS) have transformed our daily life, safety of ADS is of growing significance. While various testing approaches have emerged to enhance the ADS reliability, a crucial gap remains in understanding the accidents causes.
Externí odkaz:
http://arxiv.org/abs/2409.07774
Human-Oriented Binary Reverse Engineering (HOBRE) lies at the intersection of binary and source code, aiming to lift binary code to human-readable content relevant to source code, thereby bridging the binary-source semantic gap. Recent advancements i
Externí odkaz:
http://arxiv.org/abs/2405.19581
Autor:
Cheng, Siyuan, Tao, Guanhong, Liu, Yingqi, Shen, Guangyu, An, Shengwei, Feng, Shiwei, Xu, Xiangzhe, Zhang, Kaiyuan, Ma, Shiqing, Zhang, Xiangyu
Backdoor attack poses a significant security threat to Deep Learning applications. Existing attacks are often not evasive to established backdoor detection techniques. This susceptibility primarily stems from the fact that these attacks typically lev
Externí odkaz:
http://arxiv.org/abs/2403.17188
Autor:
Han, Jiaqi, Cen, Jiacheng, Wu, Liming, Li, Zongzhao, Kong, Xiangzhe, Jiao, Rui, Yu, Ziyang, Xu, Tingyang, Wu, Fandi, Wang, Zihe, Xu, Hongteng, Wei, Zhewei, Liu, Yang, Rong, Yu, Huang, Wenbing
Geometric graph is a special kind of graph with geometric features, which is vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physical symmetries of translations, rotations, and reflections, making them i
Externí odkaz:
http://arxiv.org/abs/2403.00485
Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are either inefficient or only concerned with the target-agnostic design of 1D
Externí odkaz:
http://arxiv.org/abs/2402.13555
Autor:
Su, Zian, Xu, Xiangzhe, Huang, Ziyang, Zhang, Zhuo, Ye, Yapeng, Huang, Jianjun, Zhang, Xiangyu
Transformer based code models have impressive performance in many software engineering tasks. However, their effectiveness degrades when symbols are missing or not informative. The reason is that the model may not learn to pay attention to the right
Externí odkaz:
http://arxiv.org/abs/2402.11842