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提出了 BehaveRec 三信号框架（因果会话 Transformer、90 天用户历史编码器、基于行为嵌入相似度的用户图 GraphSAGE），在 137M 条工业序列上研究长期行为历史何时真正有益于序列推荐，并得出约 20 次交互的实用部署阈值。
PersEvalBench introduces a benchmark testing whether LLM evaluators can reliably judge contextually appropriate use of user persona information across 403 multi-episode scenarios, finding that current evaluators—especially at detecting under-personalization—remain far behind human judgment (63.9% vs 94.4%).
The paper introduces PersonaLink, a training-free method that distills user history into a bounded persona, matching retrieval on classification tasks but not on regression, highlighting a task-type asymmetry.