Papers by Jiong Lin

    1 papers
    From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning (2026.findings-acl)

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    Challenge: Generative engines (GEs) are replacing ranked links with citation-grounded answers . current methods are unable to accumulate or transfer effective strategies across tasks and engines .
    Approach: They propose a multi-agent framework where planning, editing, and fidelity-aware evaluation serve as the execution layer.
    Outcome: The proposed framework outperforms heuristic baselines in visibility and citation fidelity on three mainstream engines.

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