20 citations · 39 across the 10 of their papers we have counts for
6 papers · 1 filter
Context-Guided Decompilation: A Step Towards Re-executability
Xiaohan Wang, Yuxin Hu, Kevin Leach
Binary decompilation plays an important role in software security analysis, reverse engineering, and malware understanding when source code is unavailable. However, existing decomp…
Enhancing Code LLM Training with Programmer Attention
Yifan Zhang, Chen Huang, Zachary Karas +3
Human attention provides valuable yet underexploited signals for code LLM training, offering a perspective beyond purely machine-driven attention. Despite the complexity and cost o…
Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation
Manish Acharya, Yifan Zhang, Kevin Leach +1
Optimizing software performance through automated code refinement offers a promising avenue for enhancing execution speed and efficiency. Despite recent advancements in LLMs, a sig…
COMCAT: Leveraging Human Judgment to Improve Automatic Documentation and Summarization
Skyler Grandel, Scott Thomas Andersen, Yu Huang +1
Software maintenance constitutes a substantial portion of the total lifetime costs of software, with a significant portion attributed to code comprehension. Software comprehension…
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization
Yifan Zhang, Jiliang Li, Zachary Karas +5
Neural code summarization leverages deep learning models to automatically generate brief natural language summaries of code snippets. The development of Transformer models has led…
Do Machines and Humans Focus on Similar Code? Exploring Explainability of Large Language Models in Code Summarization
Jiliang Li, Yifan Zhang, Zachary Karas +3
Recent language models have demonstrated proficiency in summarizing source code. However, as in many other domains of machine learning, language models of code lack sufficient expl…