AI 大模型

RAG / 检索增强生成

检索增强生成、向量检索、知识库问答和面向大模型的搜索系统。

2025-10-30 至 2025-10-30 共收录 5 篇信号源：cs.IR, cs.CL, cs.AI, cs.DB

1. 检索器与排序 2 篇

2510.25518 2025-10-30 cs.AI 88%

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

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

2510.25278 2025-10-30 cs.AR 85%

DIRC-RAG: Accelerating Edge RAG with Robust High-Density and High-Loading-Bandwidth Digital In-ReRAM Computation

Kunming Shao, Zhipeng Liao, Jiangnan Yu, Liang Zhao, Qiwei Li, Xijie Huang, Jingyu He, Fengshi Tian, Yi Zou, Xiaomeng Wang, Tim Kwang-Ting Cheng, Chi-Ying Tsui

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

Comments Accepted by 2025 IEEE/ACM ISLPED

2. 知识库问答 1 篇

2510.25621 2025-10-30 cs.CL cs.AI cs.IR 86%

FARSIQA: Faithful and Advanced RAG System for Islamic Question Answering

Mohammad Aghajani Asl, Behrooz Minaei Bidgoli

专题命中知识库问答：RAG(title,abstract)；retrieval-augmented generation(abstract,comments)；分类 cs.IR、cs.CL、cs.AI

Comments 37 pages, 5 figures, 10 tables. Keywords: Retrieval-Augmented Generation (RAG), Question Answering (QA), Islamic Knowledge Base, Faithful AI, Persian NLP, Multi-hop Reasoning, Large Language Models (LLMs)

3. 图谱与结构化RAG 1 篇

2510.25724 2025-10-30 cs.AI 57%

BambooKG: A Neurobiologically-inspired Frequency-Weight Knowledge Graph

Vanya Arikutharam, Arkadiy Ukolov

专题命中图谱与结构化RAG ：retrieval-augmented generation(abstract)；分类 cs.AI

4. RAG评测 1 篇

2412.15189 2025-10-30 cs.CL cs.CY 83%

Face the Facts! Evaluating RAG-based Pipelines for Professional Fact-Checking

Daniel Russo, Stefano Menini, Jacopo Staiano, Marco Guerini

机构 * Fondazione Bruno Kessler（布罗诺·凯塞勒基金会）； University of Trento（特伦托大学）

专题命中 RAG评测：RAG(title,abstract)；retrieval-augmented generation(abstract)；分类 cs.CL

Comments Code and data at https://github.com/drusso98/face-the-facts - Accepted for publication at INLG 2025