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。

2025-09-30 至 2025-09-30 共收录 5 篇信号源：cs.IR, cs.CL, cs.AI, cs.DB

1. RAG评测 5 篇

2509.24212 2025-09-30 cs.CL 83%

ScenarioBench: Trace-Grounded Compliance Evaluation for Text-to-SQL and RAG

Zahra Atf, Peter R Lewis

机构 * Faculty of Business and Information Technology（商业与信息技术学院）； Ontario Tech University（安大略技术大学）

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

Comments Accepted for presentation at the LLMs Meet Databases (LMD) Workshop, 35th IEEE International Conference on Collaborative Advances in Software and Computing, 2025. Workshop website: https://sites.google.com/view/lmd2025/home

2509.23233 2025-09-30 cs.CL 70%

Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Models

Sina J. Semnani, Jirayu Burapacheep, Arpandeep Khatua, Thanawan Atchariyachanvanit, Zheng Wang, Monica S. Lam

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

Comments EMNLP 2025 (Main Conference)

2509.22991 2025-09-30 cs.CL cs.AI cs.CV cs.IR cs.LG 67%

ADAM: A Diverse Archive of Mankind for Evaluating and Enhancing LLMs in Biographical Reasoning

Jasin Cekinmez, Omid Ghahroodi, Saad Fowad Chandle, Dhiman Gupta, Ehsaneddin Asgari

机构 * Qatar Computing Research Institute（卡塔尔计算研究所）； Princeton University（普林斯顿大学）； Virginia Tech（弗吉尼亚理工大学）； Amity University（阿米蒂大学）

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

2503.09598 2025-09-30 cs.CL cs.AI cs.CY 62%

How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation

Ruohao Guo, Wei Xu, Alan Ritter

机构 * Georgia Institute of Technology（佐治亚理工学院）

专题命中 RAG评测：RAG(abstract)；分类 cs.CL、cs.AI

Comments Accepted to EMNLP 2025 main conference

2509.22658 2025-09-30 cs.IR cs.AI 62%

How good are LLMs at Retrieving Documents in a Specific Domain?

Nafis Tanveer Islam, Zhiming Zhao

机构 * MultiScale Networked Systems (MNS) University of Amsterdam, Netherlands, University of Amsterdam, Netherlands（多尺度网络化系统（MNS）阿姆斯特丹大学，荷兰，阿姆斯特丹大学，荷兰）

专题命中 RAG评测：RAG(abstract)；分类 cs.IR、cs.AI

Comments Accepted at FAIEMA Conference 2025. DOI will be provided once the conference publishes the paper