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AgenticRoboRL brings coding-agent post-training to robot planners

AgenticRoboRL proposes a framework for post-training robot planners across different robot harnesses. Its training recipe combines supervised fine-tuning with multi-turn reinforcement learning, and harness-specific adapters connect planner interaction records and task outcomes to a unified RL training pipeline.

Part of the event: AgenticRoboRL: Cross-Embodiment Post-Training of Robot Planners, Success Rate Rises to 71%

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