LLM agents enable users to integrate cross-platform and offline data for personalization that outperforms single-platform baselines in proof-of-concept tests.
A survey on large language models for recommendation
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RRCM trains an LLM to dynamically retrieve from collaborative and meta memories using group relative policy optimization driven by final top-k recommendation quality.
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LLM Agents Enable User-Governed Personalization Beyond Platform Boundaries
LLM agents enable users to integrate cross-platform and offline data for personalization that outperforms single-platform baselines in proof-of-concept tests.
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RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
RRCM trains an LLM to dynamically retrieve from collaborative and meta memories using group relative policy optimization driven by final top-k recommendation quality.