RAG / 检索增强生成 - arXivDaily 专题

2510.26205 2025-11-05 cs.CL cs.AI 84%

Towards Global Retrieval Augmented Generation: A Benchmark for Corpus-Level Reasoning

Qi Luo, Xiaonan Li, Tingshuo Fan, Xinchi Chen, Xipeng Qiu

机构 * Fudan University（复旦大学）； Shanghai Innovation Institute（上海创新研究院）

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

2510.24476 2025-10-29 cs.CL cs.AI 84%

Mitigating Hallucination in Large Language Models (LLMs): An Application-Oriented Survey on RAG, Reasoning, and Agentic Systems

Yihan Li, Xiyuan Fu, Ghanshyam Verma, Paul Buitelaar, Mingming Liu

机构 * Electronic Information School, Wuhan University（武汉大学电子信息学院）； School of Computing, Dublin City University（都柏林城市大学计算机学院）； School of Public Health, Wuhan University（武汉大学公共卫生学院）； Insight Centre for Data Analytics, University of Galway（Galway大学数据分析研究中心）； Insight Centre for Data Analytics, Dublin City University（都柏林城市大学数据分析研究中心）

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

Comments 25 pages, 7 figures, 3 tables

2508.17225 2025-10-07 cs.CL cs.AI 84%

SSFO: Self-Supervised Faithfulness Optimization for Retrieval-Augmented Generation

Xiaqiang Tang, Yi Wang, Keyu Hu, Rui Xu, Chuang Li, Weigao Sun, Jian Li, Sihong Xie

机构 * The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））； Chinese Academy of Sciences（中国科学院）； Shanghai AI Lab（上海人工智能实验室）； Tencent Hunyuan（腾讯文英）

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

Comments Working in progress

2510.02549 2025-10-06 cs.CL cs.AI 84%

Knowledge-Graph Based RAG System Evaluation Framework

Sicheng Dong, Vahid Zolfaghari, Nenad Petrovic, Alois Knoll

机构 * Technical University of Munich, Robotics, Artificial Intelligence and Embedded Systems（慕尼黑技术大学，机器人，人工智能与嵌入式系统）

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

2509.14435 2025-09-26 cs.CL cs.IR 84%

Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG

Harshad Khadilkar, Abhay Gupta

机构 * Indian Institute of Technology Bombay（印度理工学院班加罗尔分校）； Indian Institute of Technology Patna（印度理工学院帕纳姆分校）

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

2509.17671 2025-09-23 cs.CL cs.AI 84%

Turk-LettuceDetect: A Hallucination Detection Models for Turkish RAG Applications

Selva Taş, Mahmut El Huseyni, Özay Ezerceli, Reyhan Bayraktar, Fatma Betül Terzioğlu

机构 * Hidden for Review（保密）

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

2410.16322 2025-09-23 cs.CL cs.AI cs.HC 84%

SouLLMate: An Application Enhancing Diverse Mental Health Support with Adaptive LLMs, Prompt Engineering, and RAG Techniques

Qiming Guo, Jinwen Tang, Wenbo Sun, Haoteng Tang, Yi Shang, Wenlu Wang

机构 * Texas A&M University - Corpus Christi（德克萨斯A&M大学-科珀斯克里斯蒂分校）； University of Missouri（密苏里大学）； Delft University of Technology（代尔夫特理工大学）； University of Texas Rio Grande Valley（德克萨斯大学里奥格兰德谷分校）

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

Comments 26 pages, 19 figures, 8 tables

2509.12168 2025-09-16 cs.CL cs.AI 84%

RAGs to Riches: RAG-like Few-shot Learning for Large Language Model Role-playing

Timothy Rupprecht, Enfu Nan, Arash Akbari, Arman Akbari, Lei Lu, Priyanka Maan, Sean Duffy, Pu Zhao, Yumei He, David Kaeli, Yanzhi Wang

机构 * Department of Electrical and Computer Engineering（电气与计算机工程系）； Northeastern University（东北大学）； Tulane University（路易斯安那州立大学）

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

2508.13107 2025-09-11 cs.CL cs.IR 84%

All for law and law for all: Adaptive RAG Pipeline for Legal Research

Figarri Keisha, Prince Singh, Pallavi, Dion Fernandes, Aravindh Manivannan, Ilham Wicaksono, Faisal Ahmad, Wiem Ben Rim

机构 * University College London（伦敦大学学院）

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

Comments submitted to NLLP 2025 Workshop

2509.07475 2025-09-10 cs.CL cs.AI 84%

HALT-RAG: A Task-Adaptable Framework for Hallucination Detection with Calibrated NLI Ensembles and Abstention

Saumya Goswami, Siddharth Kurra

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

2506.02037 2025-09-03 cs.CL cs.AI 84%

FinS-Pilot: A Benchmark for Online Financial RAG System

Feng Wang, Yiding Sun, Jiaxin Mao, Wei Xue, Danqing Xu

机构 * Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学高陵人工智能学院）； Beijing Key Laboratory of Research on Large Models and Intelligent Governance（北京大型模型与智能治理研究重点实验室）； Engineering Research Center of Next-Generation Intelligent Search and Recommendation, MOE（下一代智能搜索与推荐工程研究中心，教育部）； Tencent Inc.（腾讯公司）

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

2508.18929 2025-08-27 cs.CL cs.AI 84%

Diverse And Private Synthetic Datasets Generation for RAG evaluation: A multi-agent framework

Ilias Driouich, Hongliu Cao, Eoin Thomas

机构 * AMADEUS France（AMADEUS法国）

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

Comments ECAI 2025 TRUST AI workshop

2504.20119 2025-08-08 cs.IR cs.AI 84%

Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasets

Lorenz Brehme, Thomas Ströhle, Ruth Breu

机构 * Department of Computer Science University of Innsbruck（计算机科学系因斯布鲁克大学）

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

Comments 8 Pages. This paper has been accepted for presentation at the IEEE Swiss Conference on Data Science (SDS25)

2502.17163 2025-07-22 cs.CL cs.AI 84%

MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation

María Andrea Cruz Blandón, Jayasimha Talur, Bruno Charron, Dong Liu, Saab Mansour, Marcello Federico

机构 * Tampere University（塔尔皮奥大学）； Amazon（亚马逊）

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

Comments ACL 2025

2503.04800 2025-07-21 cs.CL cs.AI 84%

HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation

Jie Ouyang, Tingyue Pan, Mingyue Cheng, Ruiran Yan, Yucong Luo, Jiaying Lin, Qi Liu

机构 * State Key Lab of Cognitive Intelligence, University of Science and Technology of China（认知智能国家重点实验室，中国科学技术大学）

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

2501.08208 2025-07-21 cs.CL cs.AI 84%

ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems

Mohita Chowdhury, Yajie Vera He, Jared Joselowitz, Aisling Higham, Ernest Lim

机构 * Ufonia Limited（乌菲尼亚有限公司）； University of York（约克大学）

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

Comments 29 pages

2503.00781 2025-07-03 cs.IR cs.AI 84%

Towards Efficient Educational Chatbots: Benchmarking RAG Frameworks

Umar Ali Khan, Ekram Khan, Fiza Khan, Athar Ali Moinuddin

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

Comments One of the co-authors is having conflict in the submission to arXiv due to many edits (we have to make changes in evaluation strategies, i.e. section 5); in the paper there are still formatting issues

2506.21569 2025-06-30 cs.CL cs.AI 84%

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA

Weihua Xiao, Derek Ekberg, Siddharth Garg, Ramesh Karri

机构 * NYU Tandon School of Engineering（纽约大学Tandon工程学院）

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

2504.15629 2025-06-12 cs.IR cs.CL 84%

CiteFix: Enhancing RAG Accuracy Through Post-Processing Citation Correction

Harsh Maheshwari, Srikanth Tenneti, Alwarappan Nakkiran

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

2505.18581 2025-05-27 cs.CL cs.AI 84%

Removal of Hallucination on Hallucination: Debate-Augmented RAG

Wentao Hu, Wengyu Zhang, Yiyang Jiang, Chen Jason Zhang, Xiaoyong Wei, Qing Li

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

Comments Accepted by ACL 2025

2406.14783 2025-05-26 cs.IR cs.CL 84%

Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework

Zackary Rackauckas, Arthur Câmara, Jakub Zavrel

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

Comments Accepted to LLM4Eval @ SIGIR24

Journal ref Proceedings of The First Workshop on Large Language Models for Evaluation in Information Retrieval (LLM4Eval 2024) co-located with 10th International Conference on Online Publishing (SIGIR 2024)

2505.09031 2025-05-15 cs.AI cs.CL 84%

Improving the Reliability of LLMs: Combining CoT, RAG, Self-Consistency, and Self-Verification

Adarsh Kumar, Hwiyoon Kim, Jawahar Sai Nathani, Neil Roy

机构 * Computer Science and Engineering Texas A&M University（计算机科学与工程，德克萨斯农工大学）

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

2502.18635 2025-05-09 cs.LG cs.AI cs.CL 84%

Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systems

Matthew Barker, Andrew Bell, Evan Thomas, James Carr, Thomas Andrews, Umang Bhatt

机构 * Trustwise AI ； New York University（纽约大学）； The Alan Turing Institute（艾伦·图灵研究所）

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

2505.00263 2025-05-02 cs.IR cs.CL 84%

EnronQA: Towards Personalized RAG over Private Documents

Michael J. Ryan, Danmei Xu, Chris Nivera, Daniel Campos

机构 * Stanford University（斯坦福大学）； Snowflake（Snowflake公司）

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

Comments 26 pages, 4 figures, 6 tables

2504.15068 2025-04-22 cs.IR cs.CL 84%

The Great Nugget Recall: Automating Fact Extraction and RAG Evaluation with Large Language Models

Ronak Pradeep, Nandan Thakur, Shivani Upadhyay, Daniel Campos, Nick Craswell, Jimmy Lin

机构 * University of Waterloo（滑铁卢大学）； Snowflake ； Microsoft（微软）

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

Comments To appear in SIGIR 2025. Significant updates and revisions to arXiv:2411.09607

2504.07803 2025-04-11 cs.CL cs.AI cs.LG 84%

A System for Comprehensive Assessment of RAG Frameworks

Mattia Rengo, Senad Beadini, Domenico Alfano, Roberto Abbruzzese

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

Comments Technical Report, 7 pages, 2 figures, 1 table

2410.13716 2025-04-01 cs.CL cs.AI 84%

MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems

Nandan Thakur, Suleman Kazi, Ge Luo, Jimmy Lin, Amin Ahmad

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

Comments Accepted at NAACL 2025 (Main Conference)

2503.10702 2025-03-17 cs.CL cs.IR 84%

ClaimTrust: Propagation Trust Scoring for RAG Systems

Hangkai Qian, Bo Li, Qichen Wang

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

Comments 6 pages, 2 figures, 1 table

2408.01262 2025-03-05 cs.CL cs.IR 84%

RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework

Kunlun Zhu, Yifan Luo, Dingling Xu, Yukun Yan, Zhenghao Liu, Shi Yu, Ruobing Wang, Shuo Wang, Yishan Li, Nan Zhang, Xu Han, Zhiyuan Liu, Maosong Sun

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

Comments https://github.com/OpenBMB/RAGEval

2502.17125 2025-02-25 cs.CL cs.AI 84%

LettuceDetect: A Hallucination Detection Framework for RAG Applications

Ádám Kovács, Gábor Recski

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

Comments 6 pages

1. RAG评测 1199 篇

Towards Global Retrieval Augmented Generation: A Benchmark for Corpus-Level Reasoning

Mitigating Hallucination in Large Language Models (LLMs): An Application-Oriented Survey on RAG, Reasoning, and Agentic Systems

SSFO: Self-Supervised Faithfulness Optimization for Retrieval-Augmented Generation

Knowledge-Graph Based RAG System Evaluation Framework

Causal-Counterfactual RAG: The Integration of Causal-Counterfactual Reasoning into RAG

Turk-LettuceDetect: A Hallucination Detection Models for Turkish RAG Applications

SouLLMate: An Application Enhancing Diverse Mental Health Support with Adaptive LLMs, Prompt Engineering, and RAG Techniques

RAGs to Riches: RAG-like Few-shot Learning for Large Language Model Role-playing

All for law and law for all: Adaptive RAG Pipeline for Legal Research

HALT-RAG: A Task-Adaptable Framework for Hallucination Detection with Calibrated NLI Ensembles and Abstention

FinS-Pilot: A Benchmark for Online Financial RAG System

Diverse And Private Synthetic Datasets Generation for RAG evaluation: A multi-agent framework

Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasets

MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation

HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation

ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems

Towards Efficient Educational Chatbots: Benchmarking RAG Frameworks

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA

CiteFix: Enhancing RAG Accuracy Through Post-Processing Citation Correction

Removal of Hallucination on Hallucination: Debate-Augmented RAG

Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework

Improving the Reliability of LLMs: Combining CoT, RAG, Self-Consistency, and Self-Verification

Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systems

EnronQA: Towards Personalized RAG over Private Documents

The Great Nugget Recall: Automating Fact Extraction and RAG Evaluation with Large Language Models

A System for Comprehensive Assessment of RAG Frameworks

MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems

ClaimTrust: Propagation Trust Scoring for RAG Systems

RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework

LettuceDetect: A Hallucination Detection Framework for RAG Applications