RAG / 检索增强生成

PyZoBot: A Platform for Conversational Information Extraction and Synthesis from Curated Zotero Reference Libraries through Advanced Retrieval-Augmented Generation

Suad Alshammari, Lama Basalelah, Walaa Abu Rukbah, Ali Alsuhibani, Dayanjan S. Wijesinghe

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

Comments 10 pages, 2 figures. The code is provided in github and the link to the repository is provided at the end of the publication

Enhancing Document VQA Models via Retrieval-Augmented Generation

Eric López, Artemis Llabrés, Ernest Valveny

机构 * Computer Vision Center, Universitat Autònoma de Barcelona, Spain（巴塞罗那自治大学计算机视觉中心） 纠错

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

Comments Accepted at Workshop on Machine Learning in Document Analysis and Recognition (ICDAR WML 2025), Wuhan, China

WIP: Leveraging LLMs for Enforcing Design Principles in Student Code: Analysis of Prompting Strategies and RAG

Dhruv Kolhatkar, Soubhagya Akkena, Edward F. Gehringer

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

Comments Accepted for presentation at the Frontiers in Education Conference, Nashville, Tennessee, USA, 2-5 November 2025

Role of Large Language Models and Retrieval-Augmented Generation for Accelerating Crystalline Material Discovery: A Systematic Review

Agada Joseph Oche, Arpan Biswas

机构 * Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, USA（跨学科研究中心，田纳西大学，诺克斯维尔，美国） ； University of Tennessee-Oak Ridge Innovation Institute, University of Tennessee, Knoxville, USA（田纳西大学橡树岭创新研究所，田纳西大学，诺克斯维尔，美国） 纠错

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

Comments 10 pages, 2 figures

TechniqueRAG: Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

Ahmed Lekssays, Utsav Shukla, Husrev Taha Sencar, Md Rizwan Parvez

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

Comments Accepted at ACL (Findings) 2025

Enhancing Retrieval-Augmented Generation for Electric Power Industry Customer Support

Hei Yu Chan, Kuok Tou Ho, Chenglong Ma, Yujing Si, Hok Lai Lin, Sa Lei Lam

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

Comments 6 pages

DR.EHR: Dense Retrieval for Electronic Health Record with Knowledge Injection and Synthetic Data

Zhengyun Zhao, Huaiyuan Ying, Yue Zhong, Sheng Yu

机构 * Tsinghua University（清华大学） 纠错

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

Comments Model and code released upon acceptance

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat

Zezhou Yang, Ting Peng, Cuiyun Gao, Chaozheng Wang, Hailiang Huang, Yuetang Deng

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

Comments Accepted in ICSME 25 Industry Track

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective

Bowen Jin, Jinsung Yoon, Zhen Qin, Ziqi Wang, Wei Xiong, Yu Meng, Jiawei Han, Sercan O. Arik

机构 * University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； Google Cloud AI Research（谷歌云人工智能研究） ； Google DeepMind（谷歌DeepMind） ； University of Virginia（弗吉尼亚大学） 纠错

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

Comments 26 pages

PhishIntentionLLM: Uncovering Phishing Website Intentions through Multi-Agent Retrieval-Augmented Generation

Wenhao Li, Selvakumar Manickam, Yung-wey Chong, Shankar Karuppayah

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

Comments Accepted by EAI ICDF2C 2025

GRAG: Graph Retrieval-Augmented Generation

Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao

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

Comments 13 pages, 5 figures

From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry

Chetan Arora, Fanyu Wang, Chakkrit Tantithamthavorn, Aldeida Aleti, Shaun Kenyon

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

Bridging the Gap with Retrieval-Augmented Generation: Making Prosthetic Device User Manuals Available in Marginalised Languages

Ikechukwu Ogbonna, Lesley Davidson, Soumya Banerjee, Abhishek Dasgupta, Laurence Kenney, Vikranth Harthikote Nagaraja

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

Comments 5 pages, 0 figures, 0 tables

Journal ref Presented in Data Science Africa 2025 Workshop, 2025, University of Ibadan, Ibadan, Nigeria

Enhancing Android Malware Detection with Retrieval-Augmented Generation

Saraga S., Anagha M. S., Dincy R. Arikkat, Rafidha Rehiman K. A., Serena Nicolazzo, Antonino Nocera, Vinod P

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

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines

Xiwei Xu, Hans Weytjens, Dawen Zhang, Qinghua Lu, Ingo Weber, Liming Zhu

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

Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation

Michael Grohs, Adrian Rebmann, Jana-Rebecca Rehse

机构 * University of Mannheim（曼海姆大学） ； SAP Signavio 纠错

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

Comments Accepted at the BPM Forum, located at the International Conference on Business Process Management (BPM) 2025

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry

Chaozheng Wang, Zezhou Yang, Shuzheng Gao, Cuiyun Gao, Ting Peng, Hailiang Huang, Yuetang Deng, Michael Lyu

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

Comments Accepted in FSE 25 Industry Track

POISONCRAFT: Practical Poisoning of Retrieval-Augmented Generation for Large Language Models

Yangguang Shao, Xinjie Lin, Haozheng Luo, Chengshang Hou, Gang Xiong, Jiahao Yu, Junzheng Shi

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

Comments 12 pages, 7 tables and 3 figures

Hoist with His Own Petard: Inducing Guardrails to Facilitate Denial-of-Service Attacks on Retrieval-Augmented Generation of LLMs

Pan Suo, Yu-Ming Shang, San-Chuan Guo, Xi Zhang

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

Comments 11 pages, 6 figures. This work will be submitted to the IEEE for possible publication

RAGDoll: Efficient Offloading-based Online RAG System on a Single GPU

Weiping Yu, Ningyi Liao, Siqiang Luo, Junfeng Liu

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

Efficient Document Retrieval with G-Retriever

Manthankumar Solanki

机构 * University of Stuttgart（斯图加特大学） 纠错

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

Comments Extended version of a paper presented at NeurIPS 2024 (arXiv:2402.07630)

RAG-Based Fuzzing of Cross-Architecture Compilers

Rana Elnaggar, Brian Delgado, Jason M. Fung

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

Financial Analysis: Intelligent Financial Data Analysis System Based on LLM-RAG

Jingru Wang, Wen Ding, Xiaotong Zhu

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

A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought

Andrei Cristian Ionescu, Sergey Titov, Maliheh Izadi

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

Comments Accepted in The ACM International Conference on the Foundations of Software Engineering (FSE 2025) - Demo Track

Bias-Aware Agent: Enhancing Fairness in AI-Driven Knowledge Retrieval

Karanbir Singh, William Ngu

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

Automatic Teaching Platform on Vision Language Retrieval Augmented Generation

Ruslan Gokhman, Jialu Li, Youshan Zhang

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

Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook

Xu Zheng, Ziqiao Weng, Yuanhuiyi Lyu, Lutao Jiang, Haiwei Xue, Bin Ren, Danda Paudel, Nicu Sebe, Luc Van Gool, Xuming Hu

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

Comments 19 pages, 10 figures

To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation

Kaustubh D. Dhole

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

Comments 1st workshop of "Quantify Uncertainty and Hallucination in Foundation Models: The Next Frontier in Reliable AI" at ICLR 2025

Retrieval Augmented Generation with Multi-Modal LLM Framework for Wireless Environments

Muhammad Ahmed Mohsin, Ahsan Bilal, Sagnik Bhattacharya, John M. Cioffi

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

Comments Accepted @ ICC 2025

A Simplified Retriever to Improve Accuracy of Phenotype Normalizations by Large Language Models

Daniel B. Hier, Thanh Son Do, Tayo Obafemi-Ajayi

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

Comments Published by Frontiers in Digital Health

Journal ref Frontiers in Digital Health 7, (2025): 1495040. Accessed March 4, 2025