Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

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

Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently
shown to transfer well to Programming Languages (PL) and largely benefit a broad set of …

Code summarization and generation empower conversion between programming language
(PL) and natural language (NL), while code translation avails the migration of legacy code …

Benchmark datasets have a significant impact on accelerating research in programming
language tasks. In this paper, we introduce CodeXGLUE, a benchmark dataset to foster …

Current machine-learning based software vulnerability detection methods are primarily
conducted at the function-level. However, a key limitation of these methods is that they do …

A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

Memory-related vulnerabilities constitute severe threats to the security of modern software.
Despite the success of deep learning-based approaches to generic vulnerability detection …

With the great success of pre-trained models, the pretrain-then-finetune paradigm has been
widely adopted on downstream tasks for source code understanding. However, compared to …