General large language models (LLMs), represented by ChatGPT, have demonstrated
significant potential in tasks such as code generation in software engineering. This has led …

The remarkable achievements of Artificial Intelligence (AI) algorithms, particularly in
Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment …

Large language models for code (LLM4Code), which demonstrate strong performance (eg,
high accuracy) in processing source code, have significantly transformed software …

Neural Language Models of Code, or Neural Code Models (NCMs), are rapidly progressing
from research prototypes to commercial developer tools. As such, understanding the …

Causal reasoning is viewed as crucial for achieving human-level machine intelligence.
Recent advances in language models have expanded the horizons of artificial intelligence …

Trustworthiness and interpretability are inextricably linked concepts for LLMs. The more
interpretable an LLM is, the more trustworthy it becomes. However, current techniques for …

This paper discusses the limitations of evaluating Masked Language Models (MLMs) in
code completion tasks. We highlight that relying on accuracy-based measurements may …

In this work, we systematically expose and measure the inconsistency and knowledge gaps
of Large Language Models (LLMs). Specifically, we propose an automated testing …

In recent years, Large Language Models for code (LLMc) have transformed the landscape of
software engineering (SE), demonstrating significant efficacy in tasks such as code …

In recent years, tasks for automated software engineering have been achieved using Large
Language Models trained on source code, such as Seq2Seq, LSTM, GPT, T5, BART and …