Drawing inspiration from how human programmers βselectively skimβ source code during development and debugging, SWE-Pruner performs task-aware adaptive pruning for long contexts.
Our two new papers from the SJTU & Huawei: Powered by DeepSeek-V3, we've achieved a new SOTA on the SWE-Bench benchmark!
We introduce two innovative approaches: βοΈ SWE-Debate: AI agents compete and "debate" to generate the best code fix. π§ SWE-Exp: An AI agent learns from past repair "experience" to solve new issues more efficiently.