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arXiv AI By Yu Xia, Jiangfan Zhang, Jun Xiao, Julian McAuley, Xiangjun Fan

Personal-Agent Mediated Recommendation with Cross-Platform User History

Read the original on arXiv AI →

The paper introduces Personal-Agent Mediated Recommendation, a new paradigm where a personal LLM agent uses cross‑platform user history to adjust a platform’s recommendation ranking. It presents MediateRec, a benchmark for evaluating this mediation, and proposes Personal Attribution Mediation Optimization (PAMO) to balance beneficial rescues against harmful overrides. Experiments show that PAMO improves over outcome‑only reinforcement learning, achieving a better rescue‑harm trade‑off on both synthetic and real cross‑platform tests.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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