103 citations · 195 across the 8 of their papers we have counts for
10 papers
Shifting Transformation Learning for Out-of-Distribution Detection
Sina Mohseni, Arash Vahdat, Jay Yadawa
Detecting out-of-distribution (OOD) samples plays a key role in open-world and safety-critical applications such as autonomous systems and healthcare. Recently, self-supervised rep…
Machine Learning Explanations to Prevent Overtrust in Fake News Detection
Sina Mohseni, Fan Yang, Shiva Pentyala +6
Combating fake news and misinformation propagation is a challenging task in the post-truth era. News feed and search algorithms could potentially lead to unintentional large-scale…
Practical Solutions for Machine Learning Safety in Autonomous Vehicles
Sina Mohseni, Mandar Pitale, Vasu Singh +1
Autonomous vehicles rely on machine learning to solve challenging tasks in perception and motion planning. However, automotive software safety standards have not fully evolved to a…
XFake: Explainable Fake News Detector with Visualizations
Fan Yang, Shiva K. Pentyala, Sina Mohseni +6
In this demo paper, we present the XFake system, an explainable fake news detector that assists end-users to identify news credibility. To effectively detect and interpret the fake…
Predicting Model Failure using Saliency Maps in Autonomous Driving Systems
Sina Mohseni, Akshay Jagadeesh, Zhangyang Wang
While machine learning systems show high success rate in many complex tasks, research shows they can also fail in very unexpected situations. Rise of machine learning products in s…
Open Issues in Combating Fake News: Interpretability as an Opportunity
Sina Mohseni, Eric Ragan, Xia Hu
Combating fake news needs a variety of defense methods. Although rumor detection and various linguistic analysis techniques are common methods to detect false content in social med…