立场声明：推荐系统应超越以平台为中心的排序，转向个人智能体中介的推荐
Position: Recommender Systems Should Move Beyond Platform-Centric Ranking toward Personal Agent-Mediated Recommendation
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中文总结 AI 辅助
本文提出个人智能体中介推荐（PAMR）范式，主张将推荐控制权从平台端排序转向用户端证据中介，并通过概念验证实验证明源选择与受控披露能优化效用、可追溯性、曝光和成本。
中文摘要 AI 辅助
推荐系统通常被构建为排序系统：平台观察用户，构建候选集，并代表用户选择物品。这种框架掩盖了更深层次的控制分配，即平台还决定了候选访问权限、证据边界、解释以及从用户需求到推荐输出的路径。我们认为，推荐的下一个瓶颈不仅在于偏好建模，还在于对证据获取和披露的控制。我们主张“个人智能体中介推荐”（PAMR），这是一种范式，其中面向用户的个人智能体代表用户在分布式来源中发现、过滤、聚合和管理推荐证据。核心转变不仅仅是简单地从一种排序模型转向另一种，而是从平台端的物品排序转向用户端的证据中介。作为一篇立场论文，我们将PAMR定义为一种新的推荐范式，确立其边界标准，识别其核心中介决策，并提出一个以中介为中心的评估框架。在困难的Yelp餐厅推荐任务上进行的概念验证研究进一步表明，在共享的LLM排序器下，源选择和受控披露提供了最强的可观测效用-可追溯性-曝光-成本操作点。
英文摘要
Recommender systems are usually framed as ranking systems: platforms observe users, construct candidate sets, and select items on their behalf. This framing hides a deeper allocation of control, in which platforms also determine candidate access, evidence boundaries, explanations, and the path from user need to recommended output. We argue that the next bottleneck in recommendation is not only preference modeling, but control over evidence acquisition and disclosure. We argue for \textbf{Personal Agent-Mediated Recommendation} (PAMR), a paradigm in which a user-facing personal agent represents the user in discovering, filtering, aggregating, and governing recommendation evidence across distributed sources. The central shift is not simply from one ranking model to another, but from platform-side item ranking to user-side evidence mediation. As a position paper, we define PAMR as a new recommendation paradigm, establish its boundary criteria, identify its core mediation decisions, and propose a mediation-centered evaluation framework. A proof-of-concept study on hard Yelp restaurant recommendation tasks further shows that, under a shared LLM ranker, source selection and controlled disclosure provide the strongest observed utility--traceability--exposure--cost operating point.
发表机构
- University of North Carolina at Charlotte（北卡罗来纳大学夏洛特分校）
- Tsinghua University（清华大学）
- Beijing University of Posts and Telecommunications（北京邮电大学）
- University of California San Diego（加州大学圣地亚哥分校）
- Beijing Normal-Hong Kong Baptist University（北京师范大学-香港浸会大学联合国际学院）
机构由 AI 辅助整理，请以论文原文为准。
