RAG / 检索增强生成

Transformer Tafsir at QIAS 2025 Shared Task: Hybrid Retrieval-Augmented Generation for Islamic Knowledge Question Answering

Muhammad Abu Ahmad, Mohamad Ballout, Raia Abu Ahmad, Elia Bruni

机构 * QIAS 2025 Shared Task（QIAS 2025 共同任务） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(title,abstract)；hybrid retrieval(title,abstract)；RAG(abstract)；dense retrieval(abstract)

Comments Accepted at ArabicNLP 2025, co-located with EMNLP 2025

A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models

Qinggang Zhang, Shengyuan Chen, Yuanchen Bei, Zheng Yuan, Huachi Zhou, Zijin Hong, Hao Chen, Yilin Xiao, Chuang Zhou, Junnan Dong, Yi Chang, Xiao Huang

专题命中 检索器与排序 ：retrieval-augmented generation(title,abstract)；RAG(abstract)；knowledge retrieval(abstract)；分类 cs.IR、cs.CL、cs.AI

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification

Huike Zou, Haiyang Yang, Yindu Su, Liyu Chen, Chengbao Lian, Qingheng Zhang, Shuguang Han, Jufeng Chen

机构 * Xianyu of Alibaba（阿里巴巴阿里圆（Xianyu）） ； Xiaohongshu Inc.（小红书公司） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(title,abstract)；RAG(abstract)；分类 cs.IR、cs.AI

An Automated Retrieval-Augmented Generation LLaMA-4 109B-based System for Evaluating Radiotherapy Treatment Plans

Junjie Cui, Peilong Wang, Jason Holmes, Leshan Sun, Michael L. Hinni, Barbara A. Pockaj, Sujay A. Vora, Terence T. Sio, William W. Wong, Nathan Y. Yu, Steven E. Schild, Joshua R. Niska, Sameer R. Keole, Jean-Claude M. Rwigema, Samir H. Patel, Lisa A. McGee, Carlos A. Vargas, Wei Liu

机构 * Mayo Clinic Arizona（梅奥诊所亚利桑那分校） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(title,abstract)；RAG(abstract)；分类 cs.AI

Comments 16 pages, 4 figures. Submitted to npj Digital Medicine

Game-Oriented ASR Error Correction via RAG-Enhanced LLM

Yan Jiang, Yongle Luo, Qixian Zhou, Elvis S. Liu

机构 * Tencent Games（腾讯游戏） 纠错

专题命中 检索器与排序 ：RAG(title,abstract)；retrieval-augmented generation(abstract)；分类 cs.AI

Journal ref 2025 IEEE Conference on Games (CoG), Lisbon, Portugal, 2025, pp. 1-8

Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation

Kaikai An, Fangkai Yang, Liqun Li, Junting Lu, Sitao Cheng, Shuzheng Si, Lu Wang, Pu Zhao, Lele Cao, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Baobao Chang

机构 * Peking University（北京大学） ； Microsoft（微软） ； Nanjing University（南京大学） 纠错

专题命中 检索器与排序 ：retrieval augmented generation(title)；retrieval-augmented generation(abstract)；RAG(abstract)；分类 cs.AI

Comments Accepted by EMNLP 2025

An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation

Kun Zhu, Xiaocheng Feng, Xiyuan Du, Yuxuan Gu, Weijiang Yu, Haotian Wang, Qianglong Chen, Zheng Chu, Jingchang Chen, Bing Qin

机构 * Harbin Institute of Technology（哈尔滨工业大学） ； Peng Cheng Laboratory（鹏城实验室） ； Sun Yat-sen University（中山大学） ； Zhejiang University（浙江大学） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(title,abstract)；分类 cs.CL、cs.AI

Comments Accepted to ACL 2024

SEARA: An Automated Approach for Obtaining Optimal Retrievers

Zou Yuheng, Wang Yiran, Tian Yuzhu, Zhu Min, Huang Yanhua

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)；RAG(abstract)；retriever(abstract)；分类 cs.IR

OnPrem.LLM: A Privacy-Conscious Document Intelligence Toolkit

Arun S. Maiya

机构 * Institute for Defense Analyses（国防分析研究所） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)；RAG(abstract)；分类 cs.CL、cs.AI

Comments 6 pages

Bridging Language Models and Formal Methods for Intent-Driven Optical Network Design

Anis Bekri, Amar Abane, Abdella Battou, Saddek Bensalem

机构 * National Institute of Standards and Technology（美国国家标准技术研究院） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)；RAG(abstract)；分类 cs.AI

Comments Accepted at AICCSA 2025

RAR$^2$: Retrieval-Augmented Medical Reasoning via Thought-Driven Retrieval

Kaishuai Xu, Wenjun Hou, Yi Cheng, Wenjie Li

机构 * Department of Computing, The Hong Kong Polytechnic University（计算机系，香港理工大学） ； Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and Technology（可信自主系统研究院和计算机科学与工程系，南方科技大学） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)；RAG(abstract)；分类 cs.CL

Comments Accepted by EMNLP 2025 Findings

Retrieval-augmented GUI Agents with Generative Guidelines

Ran Xu, Kaixin Ma, Wenhao Yu, Hongming Zhang, Joyce C. Ho, Carl Yang, Dong Yu

机构 * Emory University（埃默里大学） ； Tencent AI Lab（腾讯AI实验室） 纠错

专题命中 检索器与排序 ：RAG(abstract)；分类 cs.CL、cs.AI

Comments Accepted to EMNLP 2025 (Main Conference)

Investigating Multi-layer Representations for Dense Passage Retrieval

Zhongbin Xie, Thomas Lukasiewicz

专题命中 检索器与排序 ：dense retrieval(abstract)；分类 cs.IR

Comments Accepted to Findings of EMNLP 2025

READER: Retrieval-Assisted Drafter for Efficient LLM Inference

Maxim Divilkovskiy, Vitaly Malygin, Sergey Zlobin, Stanislav Ilyushin, Sultan Isali, Vasily Kalugin, Nuriza Aitassova, Fei Yi, Weidi Zeng

机构 * Huawei Technologies Co., Ltd.（华为技术有限公司） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)；分类 cs.CL

Query-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking

Wuwei Zhang, Fangcong Yin, Howard Yen, Danqi Chen, Xi Ye

机构 * Princeton Language and Intelligence, Princeton University（普林斯顿语言与智能研究所，普林斯顿大学） ； The University of Texas at Austin（德克萨斯大学奥斯汀分校） 纠错

专题命中 检索器与排序 ：retriever(abstract)；分类 cs.CL

Comments EMNLP 2025; Code at https://github.com/princeton-pli/QRHead

Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification

Kumar Manas, Christian Schlauch, Adrian Paschke, Christian Wirth, Nadja Klein

机构 * Department of Mathematics and Computer Science, Freie Universität Berlin（自由大学柏林数学与计算机科学系） ； Continental Automotive Technologies GmbH, AI Lab Berlin（大陆汽车技术有限公司柏林AI实验室） ； Karlsruhe Institute of Technology, Scientific Computing Center, Methods for Big Data（卡尔斯鲁厄理工学院科学计算中心、大数据方法） ； Fraunhofer Institute for Open Communication Systems, Berlin, Germany（弗劳恩霍夫开放通信系统研究所，柏林德国） 纠错

专题命中 检索器与排序 ：retrieval-augmented generation(abstract)

Comments 17 Pages, 9 figures. Accepted to Robotics: Science and Systems(RSS), 2025

Journal ref Robotics: Science and Systems (RSS), 2025