RAG / 检索增强生成

Aligning LLMs for the Classroom with Knowledge-Based Retrieval -- A Comparative RAG Study

Amay Jain, Liu Cui, Si Chen

机构 * Student（学生） ； Downingtown STEM Academy ； Department of Computer Science（计算机科学系） ； West Chester University of Pennsylvania（宾夕法尼亚州韦斯特切斯特大学） 纠错

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

Comments This work has been submitted to the IEEE for possible publication

RAGuard: A Novel Approach for in-context Safe Retrieval Augmented Generation for LLMs

Connor Walker, Koorosh Aslansefat, Mohammad Naveed Akram, Yiannis Papadopoulos

机构 * University of Hull（赫尔大学） ； AURA CDT（AURA联合培养计划） 纠错

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

How Does Knowledge Selection Help Retrieval Augmented Generation?

Xiangci Li, Jessica Ouyang

机构 * AWS AI Labs（AWS人工智能实验室） ； University of Texas at Dallas（德克萨斯大学达拉斯分校） 纠错

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

Comments Accepted by Findings of EMNLP 2025

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing

Youssef Maklad, Fares Wael, Ali Hamdi, Wael Elsersy, Khaled Shaban

机构 * Dept. of Computer Science, Qatar University, Doha, Qatar（计算机科学系，卡塔尔大学，多哈） 纠错

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

Revisiting RAG Ensemble: A Theoretical and Mechanistic Analysis of Multi-RAG System Collaboration

Yifei Chen, Guanting Dong, Yutao Zhu, Zhicheng Dou

机构 * Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学中关村人工智能学院） 纠错

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

MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generation

Pravallika Abbineni, Saoud Aldowaish, Colin Liechty, Soroosh Noorzad, Ali Ghazizadeh, Morteza Fayazi

机构 * University of Utah（犹他大学） ； University of Michigan（密歇根大学） 纠错

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

T-GRAG: A Dynamic GraphRAG Framework for Resolving Temporal Conflicts and Redundancy in Knowledge Retrieval

Dong Li, Yichen Niu, Ying Ai, Xiang Zou, Biqing Qi, Jianxing Liu

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

Provably Secure Retrieval-Augmented Generation

Pengcheng Zhou, Yinglun Feng, Zhongliang Yang

机构 * Beijing University of Posts and Telecommunications（北京邮电大学） 纠错

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

IterKey: Iterative Keyword Generation with LLMs for Enhanced Retrieval Augmented Generation

Kazuki Hayashi, Hidetaka Kamigaito, Shinya Kouda, Taro Watanabe

机构 * Nara Institute of Science and Technology（奈良科学技術研究所） ； TDSE Inc.（TDSE公司） 纠错

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

Imagine All The Relevance: Scenario-Profiled Indexing with Knowledge Expansion for Dense Retrieval

Sangam Lee, Ryang Heo, SeongKu Kang, Dongha Lee

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

Comments Accepted to COLM 2025

RAGGED: Towards Informed Design of Scalable and Stable RAG Systems

Jennifer Hsia, Afreen Shaikh, Zhiruo Wang, Graham Neubig

机构 * Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA（卡内基梅隆大学机器学习系） ； The Language Technologies Institute, Carnegie Mellon University, Pittsburgh, USA（卡内基梅隆大学语言技术研究所） 纠错

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

Comments Project page: https://github.com/neulab/ragged

Journal ref ICML 2025

Am I on the Right Track? What Can Predicted Query Performance Tell Us about the Search Behaviour of Agentic RAG

Fangzheng Tian, Jinyuan Fang, Debasis Ganguly, Zaiqiao Meng, Craig Macdonald

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

KinyaColBERT: A Lexically Grounded Retrieval Model for Low-Resource Retrieval-Augmented Generation

Antoine Nzeyimana, Andre Niyongabo Rubungo

机构 * University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校） ； Princeton University（普林斯顿大学） 纠错

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

Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems

Hoang Pham, Thuy-Duong Nguyen, Khac-Hoai Nam Bui

机构 * Viettel Group（越通集团） ； Hanoi University of Science and Technology（河内科学技术大学） 纠错

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

DocReRank: Single-Page Hard Negative Query Generation for Training Multi-Modal RAG Rerankers

Navve Wasserman, Oliver Heinimann, Yuval Golbari, Tal Zimbalist, Eli Schwartz, Michal Irani

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

Context-Guided Dynamic Retrieval for Improving Generation Quality in RAG Models

Jacky He, Guiran Liu, Binrong Zhu, Hanlu Zhang, Hongye Zheng, Xiaokai Wang

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

Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation

Sha Li, Naren Ramakrishnan

机构 * Virginia Tech（弗吉尼亚理工大学） 纠错

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

Comments 16 pages

Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG

Kushagra Bhushan, Yatin Nandwani, Dinesh Khandelwal, Sonam Gupta, Gaurav Pandey, Dinesh Raghu, Sachindra Joshi

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

Comments 22 pages, 14 tables, to be published in NAACL 2025

Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation Systems

Sejong Kim, Hyunseo Song, Hyunwoo Seo, Hyunjun Kim

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

Comments 15 pages, 3 figures, 11 tables. Accepted at ICLR 2025 Workshop on Advances in Financial AI. Code available at https://github.com/seohyunwoo-0407/GAR

WavRAG: Audio-Integrated Retrieval Augmented Generation for Spoken Dialogue Models

Yifu Chen, Shengpeng Ji, Haoxiao Wang, Ziqing Wang, Siyu Chen, Jinzheng He, Jin Xu, Zhou Zhao

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

Does RAG Really Perform Bad For Long-Context Processing?

Kun Luo, Zheng Liu, Peitian Zhang, Hongjin Qian, Jun Zhao, Kang Liu

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

RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation

Shuting Wang, Xin Yu, Mang Wang, Weipeng Chen, Yutao Zhu, Zhicheng Dou

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

Journal ref https://aclanthology.org/volumes/2025.coling-main/

CORD: Balancing COnsistency and Rank Distillation for Robust Retrieval-Augmented Generation

Youngwon Lee, Seung-won Hwang, Daniel Campos, Filip Graliński, Zhewei Yao, Yuxiong He

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

Agentic AI-Driven Technical Troubleshooting for Enterprise Systems: A Novel Weighted Retrieval-Augmented Generation Paradigm

Rajat Khanda

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

Hybrid RAG-empowered Multi-modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-based Contract Approach

Cheng Su, Jinbo Wen, Jiawen Kang, Yonghua Wang, Yuanjia Su, Hudan Pan, Zishao Zhong, M. Shamim Hossain

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

Comments 13 pages, 7 figures

Invar-RAG: Invariant LLM-aligned Retrieval for Better Generation

Ziwei Liu, Liang Zhang, Qian Li, Jianghua Wu, Guangxu Zhu

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

Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data

Anum Afzal, Juraj Vladika, Gentrit Fazlija, Andrei Staradubets, Florian Matthes

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

Toward Optimal Search and Retrieval for RAG

Alexandria Leto, Cecilia Aguerrebere, Ishwar Bhati, Ted Willke, Mariano Tepper, Vy Ai Vo

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

Comments Accepted to NeurIPS 2024 Workshop ATTRIB

TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Network

Nouf Alabbasi, Omar Erak, Omar Alhussein, Ismail Lotfi, Sami Muhaidat, Merouane Debbah

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

SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation

Minda Hu, Licheng Zong, Hongru Wang, Jingyan Zhou, Jingjing Li, Yichen Gao, Kam-Fai Wong, Yu Li, Irwin King

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

Comments This work has been accepted by EMNLP 2024