1
Fine-grained Claim-level RAG Benchmark for Law
面向法律领域的细粒度声明级RAG基准，评估模型事实检索与推理能力的新方法。
arXiv:2605.21071v1 Announce Type: new Abstract: The rapid progress of large language models (LLMs) is shifting semantic search toward a question-answe…
2
Hiding in Plain Sight: Finding MAHA on Reddit
Reddit上隐藏着一个叫MAHA的神秘社区？这篇论文用数据挖掘方法把它揪了出来，揭秘数字暗流。
arXiv:2605.20435v1 Announce Type: cross Abstract: Make America Healthy Again (MAHA) is a national health movement that encompasses a striking mix of b…
3
LLM-Oriented Information Retrieval: A Denoising-First Perspective
面向大语言模型的信息检索新视角，首次提出以去噪为核心，提升检索质量与鲁棒性
arXiv:2605.00505v2 Announce Type: replace-cross Abstract: Modern information retrieval (IR) is no longer consumed primarily by humans but increasingly…
4
Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL
电商搜索新范式，生成式检索结合语义聚类ID与专家引导强化学习，实现端到端高效检索
arXiv:2605.14434v1 Announce Type: cross Abstract: Generative retrieval offers a promising alternative by unifying the fragmented multi-stage retrieval…
5
Thinking Ahead: Prospection-Guided Retrieval of Memory with Language Models
提出前瞻性引导的记忆检索方法，让对话助手在长周期交互中准确找回语义相似度低的关键事实，突破传统RAG回溯局限。
arXiv:2605.14177v1 Announce Type: cross Abstract: Long-horizon personalization requires dialogue assistants to retrieve user-specific facts from exten…
6
LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training
提出LLM-EDT框架，用大语言模型融入双阶段训练攻克跨域序列推荐中的不平衡与转换难题
arXiv:2511.19931v2 Announce Type: replace-cross Abstract: Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interact…