4 citations · 7 across the 5 of their papers we have counts for
5 papers
An Exploratory Study of AI System Risk Assessment from the Lens of Data Distribution and Uncertainty
Zhijie Wang, Yuheng Huang, Lei Ma +3
Deep learning (DL) has become a driving force and has been widely adopted in many domains and applications with competitive performance. In practice, to solve the nontrivial and co…
Verifying Attention Robustness of Deep Neural Networks against Semantic Perturbations
Satoshi Munakata, Caterina Urban, Haruki Yokoyama +2
It is known that deep neural networks (DNNs) classify an input image by paying particular attention to certain specific pixels; a graphical representation of the magnitude of atten…
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History
Shogo Tokui, Susumu Tokumoto, Akihito Yoshii +4
Systematic techniques to improve quality of deep neural networks (DNNs) are critical given the increasing demand for practical applications including safety-critical ones. The key…
AugmentedCode: Examining the Effects of Natural Language Resources in Code Retrieval Models
Mehdi Bahrami, N. C. Shrikanth, Yuji Mizobuchi +4
Code retrieval is allowing software engineers to search codes through a natural language query, which relies on both natural language processing and software engineering techniques…
PyTorrent: A Python Library Corpus for Large-scale Language Models
Mehdi Bahrami, N. C. Shrikanth, Shade Ruangwan +6
A large scale collection of both semantic and natural language resources is essential to leverage active Software Engineering research areas such as code reuse and code comprehensi…