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New GESE framework enhances LLM headline generation for personalized recommendations

By PulseAugur Editorial · [2 sources] ·

A new framework called GESE (Generate to Explore, Select to Exploit) has been developed to improve headline generation for personalized recommendations. This approach decouples the process into two stages: first, an LLM generates a diverse set of candidate headlines to cover a wide range of user interests, and second, a selector chooses the optimal headline based on real-time user signals. Deployed on a platform with over 100 million daily active users, GESE demonstrated significant improvements in click-through rates and dwell time compared to existing methods. AI

IMPACT This framework could improve user engagement in recommendation systems by providing more tailored content.

RANK_REASON This is a research paper detailing a new framework for LLM-based headline generation.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New GESE framework enhances LLM headline generation for personalized recommendations

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yi Chen, Rufeng Cheng, Qiang Xie, Tao Li ·

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

    arXiv:2609.15094v1 Announce Type: cross Abstract: 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 L…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Tao Li ·

    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 re…

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