LLM检索让广告推荐更稳定可预测，看论文如何用大模型优化推荐系统
arXiv:2605.21969v1 Announce Type: cross Abstract: Traditional ads recommendation systems have primarily focused on optimizing for prediction accuracy …
针对低活跃用户的推荐不确定性校准方法，有效提升冷启动场景可靠性，已被KDD 2026接收。
arXiv:2605.17788v1 Announce Type: cross Abstract: A fundamental challenge in recommender systems is balancing reliability for Low-Active Users (LAUs) …
从语义合理性到集合级效用，新框架RecoAtlas如何提升LLM推荐代理的整体推荐质量。
arXiv:2605.18805v1 Announce Type: cross Abstract: LLM recommendation agents increasingly produce structured recommendation reports: sets of items acco…
严苛重测LLM会话推荐模型，揪出语义漂移并给出缓解方案，研究方法扎实可复现。
arXiv:2605.18780v1 Announce Type: cross Abstract: Reasoning-based Large Language Models (LLMs) like PO4ISR have set new benchmarks in session-based re…
研究表明社交媒体算法推荐系统会潜移默化地改变用户语言表达方式，基于培养理论提供新视角。
arXiv:2605.17010v1 Announce Type: cross Abstract: Algorithmic feeds have become primary environments for encountering information online, yet while th…
提出UxSID模型，用语义感知对超长用户行为序列建模，显著提升推荐系统兴趣捕捉精度。
arXiv:2605.09040v3 Announce Type: replace-cross Abstract: Modeling ultra-long user sequences involves a difficult trade-off between efficiency and eff…
新动作出现时，离线上下文bandit如何优化？这篇论文提出解决方案，提升推荐系统等场景的决策效果。
arXiv:2605.18509v1 Announce Type: new Abstract: Automated decision-making algorithms drive applications such as recommendation systems and search engi…
一篇关于Agent技能全生命周期治理的论文，涵盖收集、推荐到演化，提出了SkillsVote框架。
arXiv:2605.18401v1 Announce Type: new Abstract: Long-horizon LLM agents leave traces that could become reusable experience, but raw trajectories are n…
用大模型配合检索增强，结合健康饮食指数，精准推荐个性化餐食，AI赋能营养科学。
arXiv:2605.15213v1 Announce Type: cross Abstract: Diet quality is a leading determinant of chronic disease risk. Advances in artificial intelligence (…
离策略评估的精度取决于日志策略设计，这篇论文系统研究如何优化它
arXiv:2605.15108v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target treatment policy (e.g., a recommender sy…
将推荐建模为部分可观测问题，MARS用分层信念状态记忆分离短期信号与稳定偏好，首次为记忆演化提供完整生命周期——推荐系统的记忆终于不再是一团乱麻。
arXiv:2605.14401v1 Announce Type: cross Abstract: Memory-augmented LLM agents have advanced personalized recommendation, yet existing approaches unive…