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Reasoning-Based Personalized Generation for Users with Sparse Data
稀疏数据下用推理增强个性化生成，少样本也能精准建模，推荐给做推荐系统的朋友。
arXiv:2602.21219v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) personalization holds great promise for tailoring responses by le…
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DiffGRM: Diffusion-based Generative Recommendation Model
用扩散模型替代自回归生成，为推荐系统带来全新生成范式，值得关注的WWW'26前沿研究。
arXiv:2510.21805v2 Announce Type: replace-cross Abstract: Generative recommendation (GR) is an emerging paradigm that represents each item via a token…
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Do LLM Recommenders Know When They're Hallucinating? Auditing Confidence Calibration in Catalog Faithfulness
揭秘LLM推荐系统幻觉：模型是否自知？联合审计幻觉率与置信度校准，为目录忠实度提供新视角。
arXiv:2608.10008v1 Announce Type: cross Abstract: LLM recommenders for top-$K$ item suggestion regularly emit titles outside the target catalog. Prior…
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LLM Reasoning for Subjective Tasks: Failure Modes, Mitigation, and Dynamic Reasoning Routing
LLM推理并非万能，主观任务中会失灵？这篇论文剖析失败模式并给出动态路由方案。
arXiv:2608.08889v1 Announce Type: new Abstract: Recommendation systems thrive on personalization, where ''correctness'' is rarely a binary truth but a…
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Clinician input steers AI toward accurate and harmful recommendations
临床医生反馈竟能同时提升AI建议的准确性与危害性，这项研究揭开人机协作的隐秘风险。
arXiv:2603.14158v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are entering clinical workflows, yet evaluations rarely assess …
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LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation
用大模型先验给冷启动推荐装上导航，汤普森采样不再盲猜，评论推荐效率起飞。
arXiv:2608.03382v1 Announce Type: cross Abstract: Multi-armed bandit algorithms, especially Thompson sampling, are widely used in online recommendatio…
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X-KGRank: A Knowledge Graph RAG Framework for Explainable Recommendations via Pattern Mining and LLM Re-Ranking
用知识图谱模式挖掘+LLM重排，给推荐系统装上可解释的“思维链”，直击黑箱痛点。
arXiv:2608.01732v1 Announce Type: cross Abstract: Modern recommender systems produce predictions that users cannot interrogate. The two dominant impro…
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Douyin Multimodal Embedding Model Technical Report
抖音多模态嵌入模型技术报告，揭秘工业级搜索推荐背后的向量表示学习。
arXiv:2608.02148v1 Announce Type: cross Abstract: Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and…
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LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains
无需训练，基于LLM推理的工业推荐框架，创新性利用大模型捕获用户潜在动机，解决稀疏文本领域推荐难题。
arXiv:2604.16379v2 Announce Type: replace-cross Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) …
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Nudging Sustainable Choices through LLM-Generated Recommendation Explanations
用LLM生成的推荐解释引导用户做出更环保的选择，研究揭示了AI在可持续消费中的新角色。
arXiv:2607.25726v1 Announce Type: new Abstract: Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustain…
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Serving the Long Tail: Training-Free LLM Candidate Generation for Vacation Rental Marketplaces
无需训练，LLM直接为度假租赁长尾房源生成推荐候选，破解协同过滤信号稀疏难题。
arXiv:2607.09877v1 Announce Type: new Abstract: Vacation rental marketplaces face a structural imbalance on the supply side: a small fraction of prope…
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Diversified Multinomial Logit Contextual Bandits
提出一种结合多项logit选择模型与多样性的上下文老虎机算法，在推荐系统中实现探索与多样性的平衡优化
arXiv:2607.11684v1 Announce Type: cross Abstract: Existing contextual multinomial logit (MNL) bandits model relevance-driven choice but ignore the pot…
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Tokenizing Numerical and Embedding Features for LLM RecSys
将数值和嵌入特征转化为令牌，突破LLM推荐系统的性能瓶颈。
arXiv:2607.10016v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as backbone architectures for recommender systems…
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Generative Pseudo-Labeling for Pre-Ranking with LLMs
提出一种利用大语言模型生成伪标签来优化预排序阶段的新方法，提升推荐系统效率。
arXiv:2602.20995v2 Announce Type: replace-cross Abstract: Pre-ranking is a critical stage in industrial recommendation systems, tasked with efficientl…
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Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
扩散生成式重排器，用扩散模型替代自回归推理，大幅提速同时保持推荐精度，适合大规模场景
arXiv:2607.01170v1 Announce Type: cross Abstract: Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-though…
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From "Strings" to "Things" for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems
把字符串变成实体连接，看LLM如何用三元组抽取打造个人知识图谱并提升推荐效果。
arXiv:2607.00003v1 Announce Type: cross Abstract: Personal Knowledge Graphs (PKGs) offer a privacy-preserving framework for modeling user preferences,…
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Teaching LLMs to Recommend and Defer in Underrepresented Epilepsy Care
当LLM学会在癫痫护理中“推荐”与“延迟”，医疗AI的公平性难题有了新解法
arXiv:2606.31036v1 Announce Type: new Abstract: Specialist epilepsy expertise is scarce in resource-constrained settings, making LLM-based decision su…
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Diagnosing and Mitigating Retrieval Bottlenecks in LLM-Based Cold-Start Recommendation
一项针对LLM冷启动推荐中检索瓶颈的系统性研究，提出诊断方法与缓解策略，为提升推荐系统长效性能提供新思路。
arXiv:2606.29947v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in recommender systems, with the exp…
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Towards Reliable Recommender Systems for Rating Data
探索如何提升评分数据推荐系统的可靠性，提出基于数据特性的新方法
arXiv:2412.20802v3 Announce Type: replace-cross Abstract: Recommender systems are widely used in the digital landscape to match users with content fit…