RAG / 检索增强生成

SKILL-RAG: Self-Knowledge Induced Learning and Filtering for Retrieval-Augmented Generation

Tomoaki Isoda

机构 * Tomoaki Isoda（独立研究者） 纠错

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

RAG+: Enhancing Retrieval-Augmented Generation with Application-Aware Reasoning

Yu Wang, Shiwan Zhao, Zhihu Wang, Ming Fan, Xicheng Zhang, Yubo Zhang, Zhengfan Wang, Heyuan Huang, Ting Liu

机构 * Xi’an Jiaotong University（西安交通大学） ； Huawei Technologies Ltd.（华为技术有限公司） ； Nankai University（南开大学） 纠错

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

CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Models

Feiyang Li, Peng Fang, Zhan Shi, Arijit Khan, Fang Wang, Weihao Wang, Xin Zhang, Yongjian Cui

机构 * School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China（华中科技大学计算机科学与技术学院） ； Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China（华中科技大学光电实验室） ； Department of Computer Science, Bowling Green State University, Ohio, USA（Bowling Green State University 计算机科学系） ； Department of Computer Science, Aalborg University, Aalborg, Denmark（Aalborg University 计算机科学系） ； Huawei Technologies Co., Ltd, Shenzhen, China（华为技术有限公司） 纠错

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

Typed-RAG: Type-Aware Decomposition of Non-Factoid Questions for Retrieval-Augmented Generation

DongGeon Lee, Ahjeong Park, Hyeri Lee, Hyeonseo Nam, Yunho Maeng

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

Comments Accepted to XLLM@ACL 2025

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning

Qingyun Sun, Jiaqi Yuan, Shan He, Xiao Guan, Haonan Yuan, Xingcheng Fu, Jianxin Li, Philip S. Yu

机构 * Beihang University（北航大学） ； Guangxi Normal University（广西师范大学） ； University of Illinois Chicago（伊利诺伊大学芝加哥分校） 纠错

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

Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge

Chase Fensore, Kaustubh Dhole, Joyce C Ho, Eugene Agichtein

机构 * Emory University, USA（埃默里大学） 纠错

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

Comments 4 pages, 3 tables, 2 figures. Accepted at the SIGIR LiveRAG Workshop 2025 (Submission 2664)

Reasoning RAG via System 1 or System 2: A Survey on Reasoning Agentic Retrieval-Augmented Generation for Industry Challenges

Jintao Liang, Gang Su, Huifeng Lin, You Wu, Rui Zhao, Ziyue Li

机构 * Beijing University of Posts and Telecommunications（北京邮电大学） ； University of Georgia（佐治亚大学） ； South China University of Technology（华南理工大学） ； Technical University of Munich, University of Cologne（慕尼黑技术大学、科隆大学） ； SenseTime Research（商汤科技研究院） ； Qingyuan Research Institute, Shanghai Jiaotong University（青原研究院，上海交通大学） 纠错

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

RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models

Bang An, Shiyue Zhang, Mark Dredze

机构 * Bloomberg AI（布莱尔人工智能） ； University of Maryland（马里兰大学） ； Johns Hopkins University（约翰霍普金斯大学） 纠错

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

Comments NAACL 2025

Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation

Yifan Feng, Hao Hu, Xingliang Hou, Shiquan Liu, Shihui Ying, Shaoyi Du, Han Hu, Yue Gao

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

PCA-RAG: Principal Component Analysis for Efficient Retrieval-Augmented Generation

Arman Khaledian, Amirreza Ghadiridehkordi, Nariman Khaledian

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

Comments 19 pages

LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs -- No Silver Bullet for LC or RAG Routing

Kuan Li, Liwen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Shuai Wang, Minhao Cheng

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

Comments 22 pages

Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting

Zilong Wang, Zifeng Wang, Long Le, Huaixiu Steven Zheng, Swaroop Mishra, Vincent Perot, Yuwei Zhang, Anush Mattapalli, Ankur Taly, Jingbo Shang, Chen-Yu Lee, Tomas Pfister

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

Comments Accepted to ICLR 2025

DH-RAG: A Dynamic Historical Context-Powered Retrieval-Augmented Generation Method for Multi-Turn Dialogue

Feiyuan Zhang, Dezhi Zhu, James Ming, Yilun Jin, Di Chai, Liu Yang, Han Tian, Zhaoxin Fan, Kai Chen

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

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation

Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh, Menghai Pan, Chin-Chia Michael Yeh, Guanchu Wang, Mingzhi Hu, Zhichao Xu, Yan Zheng, Mahashweta Das, Na Zou

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

OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large Language Models

Kartik Sharma, Peeyush Kumar, Yunqing Li

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

Class-RAG: Real-Time Content Moderation with Retrieval Augmented Generation

Jianfa Chen, Emily Shen, Trupti Bavalatti, Xiaowen Lin, Yongkai Wang, Shuming Hu, Harihar Subramanyam, Ksheeraj Sai Vepuri, Ming Jiang, Ji Qi, Li Chen, Nan Jiang, Ankit Jain

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

Comments 11 pages, submit to ACL

SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation

Prakhar Dixit, Tim Oates

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

Comments Accepted to the 4th MATH-AI Workshop at NeurIPS'24

Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience Report

Ayman Asad Khan, Md Toufique Hasan, Kai Kristian Kemell, Jussi Rasku, Pekka Abrahamsson

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

Comments 36 pages, 8 figures, 2 tables, and python code snippets

Optimizing and Evaluating Enterprise Retrieval-Augmented Generation (RAG): A Content Design Perspective

Sarah Packowski, Inge Halilovic, Jenifer Schlotfeldt, Trish Smith

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

Comments 6 pages, 4 figures, to be published in ICAAI 2024 conference proceedings

GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation

Brendan Hogan Rappazzo, Yingheng Wang, Aaron Ferber, Carla Gomes

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

Comments 8 pages

Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Siyun Zhao, Yuqing Yang, Zilong Wang, Zhiyuan He, Luna K. Qiu, Lili Qiu

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

P-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task

Weiye Xu, Min Wang, Wengang Zhou, Houqiang Li

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

M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions

Zheng Wang, Shu Xian Teo, Jieer Ouyang, Yongjun Xu, Wei Shi

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

Comments This paper has been accepted by ACL 2024

Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization

Hamed Zamani, Michael Bendersky

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

Comments To appear in the proceedings of SIGIR 2024

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Nirmalie Wiratunga, Ramitha Abeyratne, Lasal Jayawardena, Kyle Martin, Stewart Massie, Ikechukwu Nkisi-Orji, Ruvan Weerasinghe, Anne Liret, Bruno Fleisch

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

Comments Submitted to ICCBR'24

The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)

Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang

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

Prompt-RAG: Pioneering Vector Embedding-Free Retrieval-Augmented Generation in Niche Domains, Exemplified by Korean Medicine

Bongsu Kang, Jundong Kim, Tae-Rim Yun, Chang-Eop Kim

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

Comments 26 pages, 4 figures, 5 tables

Enhancing LLM Intelligence with ARM-RAG: Auxiliary Rationale Memory for Retrieval Augmented Generation

Eric Melz

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

Comments 8 pages

Retrieval Augmented Generation (RAG) for Fintech: Agentic Design and Evaluation

Thomas Cook, Richard Osuagwu, Liman Tsatiashvili, Vrynsia Vrynsia, Koustav Ghosal, Maraim Masoud, Riccardo Mattivi

机构 * Mastercard, Ireland 纠错

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

Comments Keywords: RAG Agentic AI Fintech NLP KB Domain-Specific Ontology Query Understanding

TrustRAG: Blockchain-Enhanced RAG via Committee-Based Credibility Scoring

TrustRAG：基于区块链的检索增强生成系统，通过委员会机制实现可信度评分

Baixiang Liu, Haotian Che, Yuan Li

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

AI总结 针对RAG系统难以验证文档可信度的问题，提出TrustRAG，结合区块链与委员会机制，通过零知识协议、安全多方计算及哈希承诺实现可验证的文档信任评分，保障关键领域决策安全。