RAG / 检索增强生成

Cluster-based Adaptive Retrieval: Dynamic Context Selection for RAG Applications

Yifan Xu, Vipul Gupta, Rohit Aggarwal, Varsha Mahadevan, Bhaskar Krishnamachari

机构 * University of Southern California（美国南加州大学） 纠错

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

CroPS: Improving Dense Retrieval with Cross-Perspective Positive Samples in Short-Video Search

CroPS：通过跨视角正样本提升密集检索（短视频搜索）

Ao Xie, Jiahui Chen, Quanzhi Zhu, Xiaoze Jiang, Zhiheng Qin, Enyun Yu, Han Li

机构 * Kuaishou Technology（快手科技） 纠错

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

AI总结 CroPS通过引入多视角正样本提升短视频检索性能，减少查询重述率，已在快手搜索部署。

Comments AAAI-2026, Oral

Retrieval Augmented Generation based context discovery for ASR

Dimitrios Siskos, Stavros Papadopoulos, Pablo Peso Parada, Jisi Zhang, Karthikeyan Saravanan, Anastasios Drosou

机构 * Information Technologies Institute, Center for Research and Technology Hellas（信息技术研究所，希腊研究中心与技术中心） ； Samsung Electronics R&D Institute UK (SRUK)（三星电子英国研发研究所（SRUK）） 纠错

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

Comments Accepted at EMNLP 2025

PropRAG: Guiding Retrieval with Beam Search over Proposition Paths

Jingjin Wang, Jiawei Han

机构 * Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign（塞比尔计算与数据科学学院，伊利诺伊大学厄巴纳-香槟分校） 纠错

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

Comments Accepted to EMNLP 2025 (Main Conference). Camera-ready version. Code and data: https://github.com/ReLink-Inc/PropRAG

Journal ref Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 6224-6239 November 4-9, 2025

Driving with Regulation: Trustworthy and Interpretable Decision-Making for Autonomous Driving with Retrieval-Augmented Reasoning

Tianhui Cai, Yifan Liu, Zewei Zhou, Haoxuan Ma, Seth Z. Zhao, Zhiwen Wu, Xu Han, Zhiyu Huang, Jiaqi Ma

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

Knowledge-Informed Automatic Feature Extraction via Collaborative Large Language Model Agents

Henrik Bradland, Morten Goodwin, Vladimir I. Zadorozhny, Per-Arne Andersen

机构 * School of Computing and Information, University of Pittsburgh, Pittsburgh, USA（计算机与信息学院，匹兹堡大学，美国匹兹堡） ； Centre for Artificial Intelligence Research, University of Agder, Grimstad, Norway（人工智能研究中心，阿格德大学，挪威格里斯塔德） 纠错

专题命中 检索器与排序 ：RAG(abstract)；分类 cs.CL、cs.AI

Comments 19 pages, 4 figures, in review

Multi-Agent Debate Strategies to Enhance Requirements Engineering with Large Language Models

Marc Oriol, Quim Motger, Jordi Marco, Xavier Franch

专题命中 检索器与排序 ：retrieval augmented generation(abstract)