SWE-Protégé: Small Language Models for Software Engineering Through Learned Expert Collaboration. NeurIPS 2026.
SWE-Protégé is a post-training framework (SFT + agentic RL) that teaches a small language model to stay the decision-maker on SWE tasks while selectively asking a strong expert model for guidance. It brings Qwen2.5-Coder-7B-Instruct to 42.4% Pass@1 on SWE-bench Verified, +25.4% over the prior SLM state of the art, with Claude Opus 4.1 as the expert. Work done at Meta.