In the past few years, significant progress has been made on deep neural networks (DNNs)
in achieving human-level performance on several long-standing tasks. With the broader …

Large language models (LLMs) have exploded a new heatwave of AI for their ability to
engage end-users in human-level conversations with detailed and articulate answers across …

The advent of sophisticated robotics and AI technology makes sending humans into
hazardous and distant environments to carry out inspections increasingly avoidable. Being …

The prosperous trend of deploying deep neural network (DNN) models to diverse hardware
platforms has boosted the development of deep learning (DL) compilers. DL compilers take …

The exponential growth of social media platforms such as Twitter and Facebook has
revolutionized textual communication and textual content publication in human society …

Deep Neural Networks (DNN) have achieved tremendous success in various software
applications. However, accompanied by outstanding effectiveness, DNN-driven software …

With the tremendous advancement of recurrent neural networks (RNN), dialogue systems
have achieved significant development. Many RNN-driven dialogue systems, such as Siri …

Due to the labor-intensive nature of manual test oracle construction, various automated
testing techniques have been proposed to enhance the reliability of Natural Language …

Quality assurance of deep neural networks (DNNs) is crucial for the deployment of DNN-
based software, especially in mission-and safety-critical tasks. Inspired by structural white …

Previous studies have shown that universal adversarial attacks can fool deep neural
networks over a large set of input images with a single human-invisible perturbation …