arXiv:2406.01304
공식 코드 · Papers with Code
CodeR: Issue Resolving with Multi-Agent and Task Graphs
원문 초록
GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper, we propose CodeR, which adopts a multi-agent framework and pre-defined task graphs to Repair & Resolve reported bugs and add new features within code Repository. On SWE-bench lite, CodeR is able to solve 28.33% of issues, when submitting only once for each issue. We examine the performance impact of each design of CodeR and offer insights to advance this research direction.
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CoreCodeBench: A Configurable Multi-Scenario Repository-Level Benchmark
SWE-Dev: Evaluating and Training Autonomous Feature-Driven Software Development
Less is More: Adaptive Program Repair with Bug Localization and Preference Learning
Repository-level Code Search with Neural Retrieval Methods
GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation
CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking
토론
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