Zobrazeno 1 - 10
of 545
pro vyhledávání: '"Xu, ShengJie"'
Contemporary adversarial attack methods face significant limitations in cross-model transferability and practical applicability. We present Watertox, an elegant adversarial attack framework achieving remarkable effectiveness through architectural div
Externí odkaz:
http://arxiv.org/abs/2412.15924
This study examines the impact of data snooping on neural networks for vulnerability detection in lifted code, building on previous research which used word2vec, and unidirectional and bidirectional transformer-based embeddings. The research specific
Externí odkaz:
http://arxiv.org/abs/2412.02048
Ransomware and other forms of malware cause significant financial and operational damage to organizations by exploiting long-standing and often difficult-to-detect software vulnerabilities. To detect vulnerabilities such as buffer overflows in compil
Externí odkaz:
http://arxiv.org/abs/2409.17513
Autor:
Xu, Shengjie, Xie, Lingxi
Antibody-drug conjugates (ADCs) have emerged as a promising class of targeted cancer therapeutics, but the design and optimization of their cytotoxic payloads remain challenging. This study introduces DumplingGNN, a novel hybrid Graph Neural Network
Externí odkaz:
http://arxiv.org/abs/2410.05278
Publikováno v:
2024 IEEE Cyber Awareness and Research Symposium (CARS), Grand Forks, ND, USA, 2024, pp. 1-8
Detecting vulnerabilities within compiled binaries is challenging due to lost high-level code structures and other factors such as architectural dependencies, compilers, and optimization options. To address these obstacles, this research explores vul
Externí odkaz:
http://arxiv.org/abs/2405.20611
Autor:
Reichart, Daniel E., Haislip, Joshua, Kouprianov, Vladimir, Fu, Ruide, Selph, Logan, Xu, Shengjie, Torian, John, Keohane, Jonathan, Janzen, Daryl, Moffett, David, Converse, Stanley
Funded by a $3M Department of Defense (DoD) National Defense Education Program (NDEP) award, we are developing and deploying on a national scale a follow-up curriculum to "Our Place In Space!", or OPIS!, in which approx. 3,500 survey-level astronomy
Externí odkaz:
http://arxiv.org/abs/2304.02545
Autor:
Xu, Shengjie, Mok, Kevin
This paper uses a simple state machine to develop a control algorithm for controlling an infant humanoid in the context of a simple model system. The algorithm is inspired by a baby who starts learning to stand and walk at 7 to 12 months of age: he o
Externí odkaz:
http://arxiv.org/abs/2211.06766
The augmented Lagrangian method (ALM) is classic for canonical convex programming problems with linear constraints, and it finds many applications in various scientific computing areas. A major advantage of the ALM is that the step for updating the d
Externí odkaz:
http://arxiv.org/abs/2205.02723
Publikováno v:
In Progress in Neuropsychopharmacology & Biological Psychiatry 20 December 2024 135
