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

In industrial recommendation feeds, presenting a static headline for an item often fails to satisfy the diverse, multimodal interests of the user population, particularly suppressing the needs of long-tail audiences. While Large Language Models (LLMs) have been integrated into recommendation for con