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DMRL: Document-Mediated Reinforcement Learning for Skill Optimization in Advertising Recommendation
Advertising recommendation requires continuously tuning complex system parameters while balancing commercial returns and user experience. Recent work has introduced large language models (LLMs) with skill documents to assist this labor-intensive process, but skill optimization remains largely prompt
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