Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

Deep Learning (DL) systems have received exponential growth in popularity and have
become ubiquitous in our everyday life. Such systems are built on top of popular DL …

Deep Learning (DL) library bugs affect downstream DL applications, emphasizing the need
for reliable systems. Generating valid input programs for fuzzing DL libraries is challenging …

We explore the novel application of Large Language Models to code optimization. We
present a 7B-parameter transformer model trained from scratch to optimize LLVM assembly …

Bugs in Deep Learning (DL) libraries may affect almost all downstream DL applications, and
it is crucial to ensure the quality of such systems. It is challenging to generate valid input …

Deep Learning (DL) has gained wide attention in recent years. Meanwhile, bugs in DL
systems can lead to serious consequences, and may even threaten human lives. As a result …

Deep-learning (DL) compilers such as TVM and TensorRT are increasingly being used to
optimize deep neural network (DNN) models to meet performance, resource utilization and …

Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality,
especially as mobile applications have become an integral part of our daily lives. Despite …

Software security poses substantial risks to our society because software has become part of
our life. Numerous techniques have been proposed to resolve or mitigate the impact of …