CodeV: Issue Resolving with Visual Data

Large Language Models (LLMs) have advanced rapidly in recent years, with their applications in software engineering expanding to more complex repository-level tasks. GitHub issue resolving is a key challenge among these tasks. While recent approaches have made progress on this task, they focus on textual data within issues, neglecting visual data. However, this visual data is crucial for resolving issues as it conveys additional knowledge that text alone cannot. We propose CODEV, the first approach to leveraging visual data to enhance the issue-resolving capabilities of LLMs. CODEV resolves each issue by following a two-phase process: data processing and patch generation. To evaluate CODEV, we construct a benchmark for visual issue resolving, namely Visual SWEbench. Through extensive experiments, we demonstrate the effectiveness of CODEV, as well as provide valuable insights into leveraging visual data to resolve GitHub issues 1 . * Corresponding authors 1 https://github.com/luolin101/CodeV PX facet labels don't respect labels kwarg #1944 px.scatter(tips, x="total_bill", y="tip", facet_row="time", facet_col="day", labels="time": "THE TIME", "day": "THE DAY")