RAG / 检索增强生成

CODE: A Contradiction-Based Deliberation Extension Framework for Overthinking Attacks on Retrieval-Augmented Generation

CODE：一种基于矛盾的 deliberation 延伸框架，用于对抗检索增强生成中的过度思考攻击

Xiaolei Zhang, Xiaojun Jia, Liquan Chen, Songze Li

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

AI总结 本文提出 CODE 框架，通过构造污染样本引发 RAG 系统的过度思考攻击，导致推理标记消耗激增，同时不影响任务性能。

Comments 12 pages with 7 figures

Utilizing Metadata for Better Retrieval-Augmented Generation

利用元数据提升检索增强生成

Raquib Bin Yousuf, Shengzhe Xu, Mandar Sharma, Andrew Neeser, Chris Latimer, 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)；分类 cs.IR、cs.CL、cs.AI

AI总结 本文提出元数据感知的检索策略，通过融合元数据与内容提升检索增强生成的效果，实验表明统一嵌入优于纯文本基线。

Comments The 48th European Conference on Information Retrieval (ECIR 2026)

Evidence-Grounded Multi-Agent Planning Support for Urban Carbon Governance via RAG

基于证据的多智能体规划支持用于城市碳治理的RAG

Yuyan Huang, Haoran Li, Yifan Lu, Ruolin Wu, Siqian Chen, Chao Liu

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

AI总结 本文提出基于RAG的多智能体规划支持系统，用于城市碳治理，通过整合异质证据提升规划效率与准确性。

PerCache: Predictive Hierarchical Cache for RAG Applications on Mobile Devices

PerCache：面向移动设备的预测性分层缓存用于检索增强生成应用

Kaiwei Liu, Liekang Zeng, Lilin Xu, Bufang Yang, Zhenyu Yan

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

AI总结 PerCache通过预测性分层缓存减少移动RAG应用的端到端延迟，实现34.4%的延迟降低和动态资源下的最优性能。

Cross-Document Topic-Aligned Chunking for Retrieval-Augmented Generation

跨文档主题对齐的分块技术用于检索增强生成

Mile Stankovic

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

AI总结 本文提出跨文档主题对齐分块技术，通过语料层面的知识重建提升检索增强生成系统的忠实度和信息密度，实验显示其在多跳推理和法律文本任务中均取得显著性能提升。

ChatIoT: Large Language Model-based Security Assistant for Internet of Things with Retrieval-Augmented Generation

ChatIoT: 基于大语言模型的物联网安全助手与检索增强生成

Ye Dong, Yan Lin Aung, Sudipta Chattopadhyay, Jianying Zhou

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

AI总结 ChatIoT是一种基于大语言模型的物联网安全助手，通过检索增强生成技术整合安全信息，提升用户在物联网安全实践中的指导与响应能力。

Comments preprint, under revision, 19 pages, 13 figures, 8 tables

Journal ref ACNS 2026

MaP-AVR: A Meta-Action Planner for Agents Leveraging Vision Language Models and Retrieval-Augmented Generation

MaP-AVR: 一种利用视觉语言模型和检索增强生成的元动作规划器

Zhenglong Guo, Yiming Zhao, Feng Jiang, Heng Jin, Zongbao Feng, Jianbin Zhou, Siyuan Xu

机构 * Li Auto 纠错

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

AI总结 MaP-AVR通过元动作规划和检索增强生成技术，提升机器人在复杂环境中的任务规划能力。

Comments 8 pages, 10 figures, This work was completed in December 2024

Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications

生物医学中的检索增强生成：技术、数据集和临床应用的综述

Jiawei He, Boya Zhang, Hossein Rouhizadeh, Yingjian Chen, Rui Yang, Jin Lu, Xudong Chen, Nan Liu, Douglas Teodoro

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

AI总结 本文综述了生物医学中检索增强生成技术的发展，探讨了其在临床应用中的挑战与未来发展方向。

Comments 49 pages

A Comparative Analysis of Retrieval-Augmented Generation Techniques for Bengali Standard-to-Dialect Machine Translation Using LLMs

基于LLMs的孟加拉语标准语到方言机器翻译中检索增强生成技术的比较分析

K. M. Jubair Sami, Dipto Sumit, Ariyan Hossain, Farig Sadeque

机构 * Department of Computer Science and Engineering（计算机科学与工程系） ； BRAC University（BRAC大学） 纠错

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

AI总结 本文提出并比较了两种RAG管道，用于孟加拉语标准语到方言的机器翻译，展示了句子对管道在低资源环境下优于转录管道的性能，且小型模型可超越大模型。

Comments Accepted to the Second Workshop on Bangla Language Processing (BLP) at IJCNLP-AACL 2025. 14 pages, 9 figures, 6 tables

OpenFOAMGPT: a RAG-Augmented LLM Agent for OpenFOAM-Based Computational Fluid Dynamics

OpenFOAMGPT：一种基于检索增强生成的LLM代理，用于基于OpenFOAM的计算流体力学

Sandeep Pandey, Ran Xu, Wenkang Wang, Xu Chu

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

AI总结 OpenFOAMGPT是一种基于检索增强生成的LLM代理，用于优化OpenFOAM的CFD模拟，通过高效处理复杂任务提升工程应用效率。

RAG-Empowered LLM-Driven Dynamic Radio Resource Management in Open 6G RAN

基于RAG的LLM驱动的开放6G RAN动态无线电资源管理

Onur Salan, Burak Çırağ, Onur Sever, İbrahim Hökelek, Ali Görçin, Hakan Ali Çırpan

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

AI总结 本文提出基于RAG的LLM驱动的O-RAN动态资源管理框架，通过双代理机制实现网络切片的自适应控制，提升计算效率和SLA合规性。

Comments Submitted to possible IEEE conferences

5G Network Automation Using Local Large Language Models and Retrieval-Augmented Generation

利用本地大语言模型和检索增强生成实现5G网络自动化

Ahmadreza Majlesara, Ali Majlesi, Ali Mamaghani, Alireza Shokrani, Babak Hossein Khalaj

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

AI总结 本研究通过本地部署大语言模型与检索增强生成技术，实现5G网络自动化管理，提升隐私保护与配置效率。

Comments 4 pages, 1 figure, demonstrated on 6G Summit Abu Dhabi

Fine-Grained Privacy Extraction from Retrieval-Augmented Generation Systems via Knowledge Asymmetry Exploitation

通过知识不对称利用从检索增强生成系统中进行细粒度隐私提取

Yufei Chen, Yao Wang, Haibin Zhang, Tao Gu

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

AI总结 本文提出一种利用知识不对称性从RAG系统中细粒度提取隐私信息的攻击框架，通过自适应提示和神经网络训练实现高隐私提取率。

ReVul-CoT: Towards Effective Software Vulnerability Assessment with Retrieval-Augmented Generation and Chain-of-Thought Prompting

ReVul-CoT：通过检索增强生成与链式推理提示实现有效的软件漏洞评估

Zhijie Chen, Xiang Chen, Ziming Li, Jiacheng Xue, Chaoyang Gao

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

AI总结 ReVul-CoT通过整合检索增强生成与链式推理提示，提升软件漏洞评估的准确性和效率。

CoEdge-RAG: Optimizing Hierarchical Scheduling for Retrieval-Augmented LLMs in Collaborative Edge Computing

Guihang Hong, Tao Ouyang, Kongyange Zhao, Zhi Zhou, Xu Chen

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

Comments Accepted by RTSS 2025 (Real-Time Systems Symposium, 2025)

Repairing Responsive Layout Failures Using Retrieval Augmented Generation

Tasmia Zerin, Moumita Asad, B. M. Mainul Hossain, Kazi Sakib

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

Comments Accepted at the 41st IEEE International Conference on Software Maintenance and Evolution 2025 (ICSME'25)

A Memory-Efficient Retrieval Architecture for RAG-Enabled Wearable Medical LLMs-Agents

Zhipeng Liao, Kunming Shao, Jiangnan Yu, Liang Zhao, Tim Kwang-Ting Cheng, Chi-Ying Tsui, Jie Yang, Mohamad Sawan

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

Comments Accepted by BioCAS2025

Data Auctions for Retrieval Augmented Generation

Minbiao Han, Seyed A. Esmaeili, Michael Albert, Haifeng Xu

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

FidelityGPT: Correcting Decompilation Distortions with Retrieval Augmented Generation

Zhiping Zhou, Xiaohong Li, Ruitao Feng, Yao Zhang, Yuekang Li, Wenbu Feng, Yunqian Wang, Yuqing Li

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

A Feasibility Study on Usability and Trust among Population Groups of a Medical Avatar Supported by Large Language Models with Retrieval Augmented Generation

Roel Boumans, Lisa Cramer, Sascha van de Poll, Henria Vermeulen

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

Comments 22 pages, 4 figures, 2 tables

Unmasking Hiring Bias: Platform Data Analysis and Controlled Experiments on Bias in Online Freelance Marketplaces via RAG-LLM Generated Contents

Wugeng Zheng, Guohou Shan

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

A Longitudinal Study on Different Annotator Feedback Loops in Complex RAG Tasks

Sara Rosenthal, Maeda Hanafi, Yannis Katsis, Lucian Popa, Marina Danilevsky

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

Comments 26 pages

Retrieval-Augmented Generation with Estimation of Source Reliability

Jeongyeon Hwang, Junyoung Park, Hyejin Park, Dongwoo Kim, Sangdon Park, Jungseul Ok

机构 * Pohang University of Science and Technology (POSTECH)（釜山科学技术大学） 纠错

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

NotebookLM as a Socratic physics tutor: Design and preliminary observations of a RAG-based tool

Eugenio Tufino

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

Comments 9 pages, 5 figures. Revised version accepted for publication in The Physics Educator (World Scientific, in press)

Advancing TTP Analysis: Harnessing the Power of Large Language Models with Retrieval Augmented Generation

Reza Fayyazi, Rozhina Taghdimi, Shanchieh Jay Yang

机构 * Department of Electrical & Computer Engineering（电气与计算机工程系） ； Rochester Institute of Technology（罗切斯特理工学院） 纠错

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

ARRC: Advanced Reasoning Robot Control - Knowledge-Driven Autonomous Manipulation Using Retrieval-Augmented Generation

Eugene Vorobiov, Ammar Jaleel Mahmood, Salim Rezvani, Robin Chhabra

机构 * Department of Mechanical, Industrial and Mechatronics Engineering, Toronto Metropolitan University（机械、工业与机电工程系，多伦多 Metropolitan 大学） 纠错

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

Bridging Clinical Narratives and ACR Appropriateness Guidelines: A Multi-Agent RAG System for Medical Imaging Decisions

Satrio Pambudi, Filippo Menolascina

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

Online-Optimized RAG for Tool Use and Function Calling

Yu Pan, Xiaocheng Li, Hanzhao Wang

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

Seeing the Forest Through the Trees: Knowledge Retrieval for Streamlining Particle Physics Analysis

James McGreivy, Blaise Delaney, Anja Beck, Mike Williams

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

Comments 17 pages, 3 figures

NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings

Or Shachar, Uri Katz, Yoav Goldberg, Oren Glickman

机构 * Computer Science Department, Bar-Ilan University（巴伊兰大学计算机科学系） 纠错

专题命中 检索器与排序 ：retriever(title,abstract)；分类 cs.IR、cs.CL、cs.AI

Comments Findings of EMNLP 2025