A new dual-loop framework called Mastermind has been introduced to enhance the ability of software engineering agents to reproduce repository-scale vulnerabilities. This framework separates strategy learning from task-specific experience, allowing a trainable planner to learn reusable strategies that can improve multiple frozen executors. Evaluations on CyberGym demonstrated that Mastermind, when used with GPT-5.5, achieved an 84.5% pass rate, significantly outperforming other methods. AI
IMPACT This research could lead to more effective AI agents for software engineering tasks, improving code security and development efficiency.
RANK_REASON The cluster describes a new research paper detailing a novel framework and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]
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