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LEGO-RL boosts coding agent performance by up to 8.4% while ensuring robust training signals and execution reliability.
Agentic code review can transform AI-generated pull requests into high-quality solutions, outperforming traditional methods in both accuracy and usefulness.
LLMs can generate significantly better software patches by first distilling issue descriptions into structured, refined requirements.
