RAG / 检索增强生成

Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts

Zhenghao Liu, Xingsheng Zhu, Tianshuo Zhou, Xinyi Zhang, Xiaoyuan Yi, Yukun Yan, Ge Yu, Maosong Sun

机构 * Northeastern University, China（东北大学） ； Microsoft Research Asia（微软亚洲研究院） ； Tsinghua University（清华大学） 纠错

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

RAIDX: A Retrieval-Augmented Generation and GRPO Reinforcement Learning Framework for Explainable Deepfake Detection

Tianxiao Li, Zhenglin Huang, Haiquan Wen, Yiwei He, Shuchang Lyu, Baoyuan Wu, Guangliang Cheng

机构 * University of Liverpool（利物浦大学） ； Beihang University（北航大学） ； The Chinese University of Hong Kong（香港中文大学） 纠错

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

PAIRS: Parametric-Verified Adaptive Information Retrieval and Selection for Efficient RAG

Wang Chen, Guanqiang Qi, Weikang Li, Yang Li, Deguo Xia, Jizhou Huang

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

Towards Temporal-Aware Multi-Modal Retrieval Augmented Generation in Finance

Fengbin Zhu, Junfeng Li, Liangming Pan, Wenjie Wang, Fuli Feng, Chao Wang, Huanbo Luan, Tat-Seng Chua

机构 * National University of Singapore（新加坡国立大学） ； Peking University（北京大学） ； University of Science and Technology of China（中国科学技术大学） ； Estates Pte Ltd（6Estates私人有限公司） 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 MM 2025

GETALP@AutoMin 2025: Leveraging RAG to Answer Questions based on Meeting Transcripts

Jeongwoo Kang, Markarit Vartampetian, Felix Herron, Yongxin Zhou, Diandra Fabre, Gabriela Gonzalez-Saez

机构 * Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG（格勒诺布尔阿尔卑斯大学、国家科学研究中心、格勒诺布尔理工大学、LIG实验室） 纠错

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

Efficacy of AI RAG Tools for Complex Information Extraction and Data Annotation Tasks: A Case Study Using Banks Public Disclosures

Nicholas Botti, Flora Haberkorn, Charlotte Hoopes, Shaun Khan

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

Advanced System Integration: Analyzing OpenAPI Chunking for Retrieval-Augmented Generation

Robin D. Pesl, Jerin G. Mathew, Massimo Mecella, Marco Aiello

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 This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this contribution is published in Advanced Information Systems Engineering. CAiSE 2025. Lecture Notes in Computer Science, vol 15702. Springer, Cham., and is available online at https://doi.org/10.1007/978-3-031-94571-7_8

Journal ref Advanced Information Systems Engineering. CAiSE 2025. Lecture Notes in Computer Science, vol 15702. Springer, Cham

Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generation

Xin Zhang, Lissette Iturburu, Juan Nicolas Villamizar, Xiaoyu Liu, Manuel Salmeron, Shirley J. Dyke, Julio Ramirez

机构 * Lyles School of Civil and Construction Engineering（莱尔斯土木与建设工程学院） ； Purdue University（普渡大学） ； School of Mechanical Engineering（机械工程学院） 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

KnowShiftQA: How Robust are RAG Systems when Textbook Knowledge Shifts in K-12 Education?

Tianshi Zheng, Weihan Li, Jiaxin Bai, Weiqi Wang, Yangqiu Song

机构 * Department of Computer Science and Engineering, HKUST, Hong Kong SAR, China（计算机科学与工程系，香港科技大学，香港特别行政区，中国） ； Department of Mechanical Engineering, The University of Tokyo, Tokyo, Japan（机械工程系，东京大学，东京，日本） 纠错

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

Comments ACL 2025 Main

A Library of LLM Intrinsics for Retrieval-Augmented Generation

Marina Danilevsky, Kristjan Greenewald, Chulaka Gunasekara, Maeda Hanafi, Lihong He, Yannis Katsis, Krishnateja Killamsetty, Yulong Li, Yatin Nandwani, Lucian Popa, Dinesh Raghu, Frederick Reiss, Vraj Shah, Khoi-Nguyen Tran, Huaiyu Zhu, Luis Lastras

机构 * IBM Research（IBM研究院） 纠错

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

Comments This (June 2025) is the second version of this paper (the first was published in April 2025). Intrinsics implemented as LoRAs are now trained on IBM Granite 3.3 8b instruct (previously 3.2)

HedraRAG: Coordinating LLM Generation and Database Retrieval in Heterogeneous RAG Serving

Zhengding Hu, Vibha Murthy, Zaifeng Pan, Wanlu Li, Xiaoyi Fang, Yufei Ding, Yuke Wang

机构 * University of California San Diego（加州大学圣地亚哥分校） ； Rice University（里士满大学） 纠错

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

Comments Accepted by SOSP 2025

Good/Evil Reputation Judgment of Celebrities by LLMs via Retrieval Augmented Generation

Rikuto Tsuchida, Hibiki Yokoyama, Takehito Utsuro

机构 * Grad. Sch. Sci.&Tech., University of Tsukuba（大学理工学院） 纠错

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

Evaluating Retrieval-Augmented Generation Agents for Autonomous Scientific Discovery in Astrophysics

Xueqing Xu, Boris Bolliet, Adrian Dimitrov, Andrew Laverick, Francisco Villaescusa-Navarro, Licong Xu, Íñigo Zubeldia

机构 * Institute of Astronomy, University of Cambridge, Cambridge, United Kingdom（英国剑桥大学天文研究所） ； Kavli Institute for Cosmology, University of Cambridge, Cambridge, United Kingdom（英国剑桥大学卡弗里宇宙研究所） ； Department of Physics, University of Cambridge, Cambridge, United Kingdom（英国剑桥大学物理系） ； Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA（Flatiron研究所计算天体物理学中心） ； Department of Astrophysical Sciences, Princeton University, Princeton, NJ, USA（普林斯顿大学天体物理学系） 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 contribution (spotlight) to the ICML 2025 Workshop on Machine Learning for Astrophysics; codes: https://huggingface.co/datasets/ASTROANTS/CosmoPaperQA, https://github.com/CMBAgents/cmbagent, https://github.com/CMBAgents/scirag

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level

Sezen Perçin, Xin Su, Qutub Sha Syed, Phillip Howard, Aleksei Kuvshinov, Leo Schwinn, Kay-Ulrich Scholl

机构 * Technical University of Munich（慕尼黑技术大学） ； Intel Labs（英特尔实验室） ； Thoughtworks 纠错

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

Comments Accepted to Generation, Evaluation & Metrics (GEM) Workshop at ACL 2025

KERAG_R: Knowledge-Enhanced Retrieval-Augmented Generation for Recommendation

Zeyuan Meng, Zixuan Yi, Iadh Ounis

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

The Hidden Threat in Plain Text: Attacking RAG Data Loaders

Alberto Castagnaro, Umberto Salviati, Mauro Conti, Luca Pajola, Simeone Pizzi

机构 * University of Padua（帕多瓦大学） 纠错

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

Comments currently under submission

UrbanMind: Towards Urban General Intelligence via Tool-Enhanced Retrieval-Augmented Generation and Multilevel Optimization

Kai Yang, Zelin Zhu, Chengtao Jian, Hui Ma, Shengjie Zhao, Xiaozhou Ye, Ye Ouyang

机构 * Tongji University（同济大学） ； Xinjiang University（新疆大学） ； Asiainfo Technologies（亚洲信息科技） 纠错

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

From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM

Xinyi Wu, Yanhao Jia, Luwei Xiao, Shuai Zhao, Fengkuang Chiang, Erik Cambria

机构 * School of Education, Shanghai Jiao Tong University（上海交通大学教育学院） ； College of Computing and Data Science, Nanyang Technological University（南洋理工大学 computing and Data Science 学院） ； school of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院） 纠错

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

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Fangyuan Zhang, Zhengjun Huang, Yingli Zhou, Qintian Guo, Zhixun Li, Wensheng Luo, Di Jiang, Yixiang Fang, Xiaofang Zhou

机构 * Huawei Hong Kong Research Center（华为香港研究中心） ； The Hong Kong University of Science and Technology（香港理工大学） ； The Chinese University of Hong Kong-Shenzhen（香港中文大学（深圳）） ； The Chinese University of Hong Kong（香港中文大学） ； Hunan University（湖南大学） 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.IR

Comments Under review

Question Decomposition for Retrieval-Augmented Generation

Paul J. L. Ammann, Jonas Golde, Alan Akbik

机构 * Humboldt-Universität zu Berlin（柏林洪堡大学） 纠错

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

Comments Accepted to ACL SRW 2025. 9 Pages, 2 Figures, 4 Tables

Machine Assistant with Reliable Knowledge: Enhancing Student Learning via RAG-based Retrieval

Yongsheng Lian

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

Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality

Naihe Feng, Yi Sui, Shiyi Hou, Jesse C. Cresswell, Ga Wu

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

Comments Accepted by SIGIR 2025 short paper, 5 pages, Code is available at https://github.com/n4feng/ResponseQualityAssessment

heiDS at ArchEHR-QA 2025: From Fixed-k to Query-dependent-k for Retrieval Augmented Generation

Ashish Chouhan, Michael Gertz

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

Comments 12 pages, 2 figures, 6 tables, Workshop on BioNLP and Shared Tasks at ACL 2025

GenDFIR: Advancing Cyber Incident Timeline Analysis Through Retrieval Augmented Generation and Large Language Models

Fatma Yasmine Loumachi, Mohamed Chahine Ghanem, Mohamed Amine Ferrag

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 24 pages V5.3

SGIC: A Self-Guided Iterative Calibration Framework for RAG

Guanhua Chen, Yutong Yao, Lidia S. Chao, Xuebo Liu, Derek F. Wong

机构 * NLP 2 CT Lab, Department of Computer and Information Science, University of Macau（自然语言处理2CT实验室，计算机与信息科学系，澳门大学） ； Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China（计算与智能学院，哈尔滨工业大学深圳校区，中国） 纠错

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

RePCS: Diagnosing Data Memorization in LLM-Powered Retrieval-Augmented Generation

Le Vu Anh, Nguyen Viet Anh, Mehmet Dik, Luong Van Nghia

机构 * 1 Institute of Information Technology, Vietnam Academy of Science ； 2 Institute of Information Technology, Vietnam Academy of Science ； 3 Department of Mathematics, Computer Science \& Physics, Rockford University, Illinois, United States Email ； 4 Department of Information Technology, Dong A University, Da Nang, Vietnam Email 纠错

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

Comments 11 pages, 7 figures, 5 tables

Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG

Xueying Du, Geng Zheng, Kaixin Wang, Yi Zou, Yujia Wang, Wentai Deng, Jiayi Feng, Mingwei Liu, Bihuan Chen, Xin Peng, Tao Ma, Yiling Lou

机构 * Fudan University（复旦大学） ； Alibaba Group（阿里巴巴集团） ； Sun Yat-sen University（中山大学） 纠错

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

Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation

Xiaofan Zhou, Liangjie Huang, Pinyang Cheng, Wenpen Yin, Rui Zhang, Wenrui Hao, Lu Cheng

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

Comments 9 pages, under review

Why Uncertainty Estimation Methods Fall Short in RAG: An Axiomatic Analysis

Heydar Soudani, Evangelos Kanoulas, Faegheh Hasibi

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

Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation

Yucheng Chu, Peng He, Hang Li, Haoyu Han, Kaiqi Yang, Yu Xue, Tingting Li, Joseph Krajcik, Jiliang Tang

机构 * Michigan State University（密歇根州立大学） ； Washington State University（华盛顿州立大学） 纠错

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

Comments EDM 2025 Short Paper