Abstract: In this work, we introduce a novel large language model (LLM)-based masking mutation operator for Genetic Improvement (GI), which leverages code completion capabilities of large language ...

Abstract: In rapidly evolving field of vision-language models (VLMs), contrastive language-image pre-training (CLIP) has made significant strides, becoming foundation for various downstream tasks.

Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for ...