AIBullisharXiv – CS AI · Jun 237/10
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Steer, Don't Solve: Training Small Critic Models for Large Code Agents
Researchers developed a small critic model that guides large code agents during execution rather than evaluating completed work, reducing computational costs while improving performance. The approach achieves 25.2% accuracy on SWE-bench Verified at 64% lower expense than larger agents, demonstrating that supplementing agent training with efficient feedback mechanisms outperforms scaling alone.
🏢 Hugging Face