---
id: 20260302-T0-12
title: "U-CAN：基于效用感知对比衰减的生成式推荐高效遗忘"
title_en: "U-CAN: Utility-Aware Forgetting for Generative Recommenders"
url: https://ai.daily.yangsir.net/daily/20260302-T0-12
issue_date: 2026-03-02
publish_date: 2026-03-02T05:00:00.000Z
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2602.23400
---

# U-CAN：基于效用感知对比衰减的生成式推荐高效遗忘

U-CAN是一种针对生成式推荐系统的用户数据遗忘方法。该研究通过效用感知对比衰减技术，在保留模型推荐功能的同时精准移除用户敏感信息。实验证明，该方法能在不显著降低推荐准确率的情况下，有效减少敏感属性编码，适用于隐私保护场景。企业可用该技术合规处理用户日志，避免数据泄露风险。

## English Version

**U-CAN: Utility-Aware Forgetting for Generative Recommenders**

U-CAN is a user data forgetting method for generative recommendation systems. It uses utility-aware contrastive decay to precisely remove sensitive user information while preserving recommendation functionality. Experiments prove it effectively reduces sensitive attribute encoding without significantly lowering recommendation accuracy, making it suitable for privacy protection scenarios. Companies can use this technology to compliantly process user logs and prevent data leakage risks.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2602.23400)

**详情页**：https://ai.daily.yangsir.net/daily/20260302-T0-12

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