Zobrazeno 1 - 10
of 114 426
pro vyhledávání: '"A, Tse"'
With increasing revelations of academic fraud, detecting forged experimental images in the biomedical field has become a public concern. The challenge lies in the fact that copy-move targets can include background tissue, small foreground objects, or
Externí odkaz:
http://arxiv.org/abs/2412.10258
Graphical User Interfaces (GUIs) are the primary means by which users interact with mobile applications, making them crucial to both app functionality and user experience. However, a major challenge in automated testing is the frequent appearance of
Externí odkaz:
http://arxiv.org/abs/2412.02933
We present a framework for investigating the effects of interactions on crystalline symmetry-protected topological (SPT) phases. Within this framework, one can establish a direct connection between the equivalence classes of free-fermion systems and
Externí odkaz:
http://arxiv.org/abs/2411.19287
We explore one-dimensional fermionic symmetry-protected topological (SPT) phases related by the crystalline equivalence principle. In particular, we study charge-conserving many-body topological phases of fermions protected respectively by chiral and
Externí odkaz:
http://arxiv.org/abs/2411.19268
We theoretically investigate the second harmonic generation (SHG) of topological insulator surface states in a perpendicular magnetic field. Our theory is based on the microscopic expression of the second-order magneto-optical conductivity developed
Externí odkaz:
http://arxiv.org/abs/2411.17346
Autor:
Mondal, Shouvick, Chen, Tse-Hsun
Test case prioritization (TCP) has been an effective strategy to optimize regression testing. Traditionally, test cases are ordered based on some heuristic and rerun against the version under test with the goal of yielding a high failure throughput.
Externí odkaz:
http://arxiv.org/abs/2412.00015
In this study, we revisit the commonly-cited off-target issue in multilingual neural machine translation (MNMT). By carefully designing experiments on different MNMT scenarios and models, we attribute the off-target issue to the overfitting of the sh
Externí odkaz:
http://arxiv.org/abs/2411.10581
Autor:
Liu, Zhen-Ting, Chen, Shang-Tse
Model Inversion (MI) attacks pose a significant threat to the privacy of Deep Neural Networks by recovering training data distribution from well-trained models. While existing defenses often rely on regularization techniques to reduce information lea
Externí odkaz:
http://arxiv.org/abs/2411.08460
Autor:
Lin, Lingrui, Lelli, Federico, De Breuck, Carlos, Man, Allison, Zhang, Zhi-Yu, Santini, Paola, Marasco, Antonino, Castellano, Marco, Nesvadba, Nicole, Bisbas, Thomas G., Huang, Hao-Tse, Lehnert, Matthew
The gas dynamics of galaxies provide critical insights into the evolution of both baryons and dark matter (DM) across cosmic time. In this context, galaxies at cosmic noon -- the period characterized by the most intense star formation and black hole
Externí odkaz:
http://arxiv.org/abs/2411.08958
Reusing third-party libraries increases productivity and saves time and costs for developers. However, the downside is the presence of vulnerabilities in those libraries, which can lead to catastrophic outcomes. For instance, Apache Log4J was found t
Externí odkaz:
http://arxiv.org/abs/2411.07480