2 citations · 3 across the 2 of their papers we have counts for
3 papers
Automatically Detecting Numerical Instability in Machine Learning Applications via Soft Assertions
Shaila Sharmin, Anwar Hossain Zahid, Subhankar Bhattacharjee +3
Machine learning (ML) applications have become an integral part of our lives. ML applications extensively use floating-point computation and involve very large/small numbers; thus,…
ActiveClean: Generating Line-Level Vulnerability Data via Active Learning
Ashwin Kallingal Joshy, Mirza Sanjida Alam, Shaila Sharmin +2
Deep learning vulnerability detection tools are increasing in popularity and have been shown to be effective. These tools rely on large volume of high quality training data, which…
Do Language Models Learn Semantics of Code? A Case Study in Vulnerability Detection
Benjamin Steenhoek, Md Mahbubur Rahman, Shaila Sharmin +1
Recently, pretrained language models have shown state-of-the-art performance on the vulnerability detection task. These models are pretrained on a large corpus of source code, then…