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Doing More with Less Tokens: Hierarchical Reinforcement Learning for Efficient Coding Agents
Recently, coding agents have emerged as a dominant paradigm for real-world software engineering (SWE) scenarios, which solve complex tasks through multi-turn interactions with development environments. However, frequent interactions with environments would inevitably introduce substantial token over
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