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#artificial intelligence Preprint Sep 2026

Generate to Explore, Select to Exploit: Aligning LLM-based Headline Generation with Personalized Recommendation

GESE (Generate to Explore, Select to Exploit), a framework operating at the system's presentation layer that decouples personalization into generative exploration and selective exploitation, validate that decoupling diversity-oriented generation from precision-oriented selection offers a robust blueprint for aligning g...

Yi Chen, Ru-Feng Cheng, Qiang Xie et al. · 0 citations

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