RAG / 检索增强生成

LLM-based Query Expansion Fails for Unfamiliar and Ambiguous Queries

Kenya Abe, Kunihiro Takeoka, Makoto P. Kato, Masafumi Oyamada

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

Comments Accepted at SIGIR 2025 short paper track

CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability

Han Peng, Jinhao Jiang, Zican Dong, Wayne Xin Zhao, Lei Fang

机构 * Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学人工智能学院） 纠错

专题命中 检索器与排序 ：RAG(abstract)；分类 cs.CL

Disentangling Memory and Reasoning Ability in Large Language Models

Mingyu Jin, Weidi Luo, Sitao Cheng, Xinyi Wang, Wenyue Hua, Ruixiang Tang, William Yang Wang, Yongfeng Zhang

机构 * Rutgers University（罗格斯大学） ； The Ohio State University（俄亥俄州立大学） ； University of California, Santa Barbara（加州大学圣巴巴拉分校） 纠错

专题命中 检索器与排序 ：knowledge retrieval(abstract)；分类 cs.CL

Comments Accepted by ACL 2025

Conversational Query Reformulation with the Guidance of Retrieved Documents

Jeonghyun Park, Hwanhee Lee

机构 * Department of Artificial Intelligence, Chung-Ang University, Seoul, Korea（人工智能系， Chung-Ang 大学） 纠错

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

Comments 18 pages, 3 figures, 16 tables

Scaling Context, Not Parameters: Training a Compact 7B Language Model for Efficient Long-Context Processing

Chen Wu, Yin Song

机构 * Amazon Web Services（亚马逊网络服务） 纠错

专题命中 检索器与排序 ：RAG(abstract)；分类 cs.CL

Comments 8 pages, 6 figures, ACL 2025 (Industry Track)

TrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matching

Majd Abdallah, Sigve Nakken, Mariska Bierkens, Johanna Galvis, Alexis Groppi, Slim Karkar, Lana Meiqari, Maria Alexandra Rujano, Steve Canham, Rodrigo Dienstmann, Remond Fijneman, Eivind Hovig, Gerrit Meijer, Macha Nikolski

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

Towards Brain Passage Retrieval -- An Investigation of EEG Query Representations

Niall McGuire, Yashar Moshfeghi

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

ScaleMCP: Dynamic and Auto-Synchronizing Model Context Protocol Tools for LLM Agents

Elias Lumer, Anmol Gulati, Vamse Kumar Subbiah, Pradeep Honaganahalli Basavaraju, James A. Burke

机构 * PricewaterhouseCoopers, U.S.A.（普华永道美国公司） 纠错

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

Comments 17 pages

Stealthy LLM-Driven Data Poisoning Attacks Against Embedding-Based Retrieval-Augmented Recommender Systems

Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio

专题命中 检索器与排序 ：RAG(abstract)；分类 cs.IR

Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets

Mandeep Rathee, V Venktesh, Sean MacAvaney, Avishek Anand

专题命中 检索器与排序 ：hybrid retrieval(abstract)；分类 cs.IR

Comments Accepted for publication at SIGIR'25 . 11 pages,5 figures, 4 tables

Hypencoder: Hypernetworks for Information Retrieval

Julian Killingback, Hansi Zeng, Hamed Zamani

机构 * University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校） 纠错

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

Towards Optimal Circuit Generation: Multi-Agent Collaboration Meets Collective Intelligence

Haiyan Qin, Jiahao Feng, Xiaotong Feng, Wei W. Xing, Wang Kang

机构 * National Key Laboratory of Spintronics, Hangzhou International Innovation Institute（国家磁电子键实验室、杭州国际创新研究院；集成电路科学与工程学院，北京航空航天大学） ； School of Integrated Circuit Science and Engineering, Beihang University（机械电子工程学院，武汉理工大学） ； School of Mechanical and Electronic Engineering, Wuhan University of Technology（数学与物理科学学院，谢菲尔德大学） ； School of Mathematical and Physical Sciences, University of Sheffield 纠错

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

Comments 9 pages, 6 figures

MADGEN: Mass-Spec attends to De Novo Molecular generation

Yinkai Wang, Xiaohui Chen, Liping Liu, Soha Hassoun

机构 * Department of Computer Science（计算机科学系） 纠错

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

Comments ICLR 2025

Replication and Exploration of Generative Retrieval over Dynamic Corpora

Zhen Zhang, Xinyu Ma, Weiwei Sun, Pengjie Ren, Zhumin Chen, Shuaiqiang Wang, Dawei Yin, Maarten de Rijke, Zhaochun Ren

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

Comments Accepted at SIGIR 2025 (Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval)

PolicyEvol-Agent: Evolving Policy via Environment Perception and Self-Awareness with Theory of Mind

Yajie Yu, Yue Feng

机构 * School of Computer Science University of Birmingham（计算机科学学院 英国伯明翰大学） 纠错

专题命中 检索器与排序 ：knowledge retrieval(abstract)；分类 cs.AI

SSFF: Investigating LLM Predictive Capabilities for Startup Success through a Multi-Agent Framework with Enhanced Explainability and Performance

Xisen Wang, Yigit Ihlamur, Fuat Alican

机构 * University of Oxford（牛津大学） ； Vela Partners 纠错

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

Comments For relevant code: https://github.com/Xisen-Wang/Startup-Success-Forecasting-Framework

Reinforcing Compositional Retrieval: Retrieving Step-by-Step for Composing Informative Contexts

Quanyu Long, Jianda Chen, Zhengyuan Liu, Nancy F. Chen, Wenya Wang, Sinno Jialin Pan

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

Comments 19 pages, 8 figures

PestMA: LLM-based Multi-Agent System for Informed Pest Management

Hongrui Shi, Shunbao Li, Zhipeng Yuan, Po Yang

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

Comments 10 pages

Review of Case-Based Reasoning for LLM Agents: Theoretical Foundations, Architectural Components, and Cognitive Integration

Kostas Hatalis, Despina Christou, Vyshnavi Kondapalli

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

REANIMATOR: Reanimate Retrieval Test Collections with Extracted and Synthetic Resources

Björn Engelmann, Fabian Haak, Philipp Schaer, Mani Erfanian Abdoust, Linus Netze, Meik Bittkowski

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

Precise Legal Sentence Boundary Detection for Retrieval at Scale: NUPunkt and CharBoundary

Michael J Bommarito, Daniel Martin Katz, Jillian Bommarito

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

Comments 12 pages, 5 figures, 6 tables

LLM-VPRF: Large Language Model Based Vector Pseudo Relevance Feedback

Hang Li, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

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

Uncovering the Limitations of Query Performance Prediction: Failures, Insights, and Implications for Selective Query Processing

Adrian-Gabriel Chifu, Sébastien Déjean, Josiane Mothe, Moncef Garouani, Diego Ortiz, Md Zia Ullah

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

Comments 18 pages, 4 figures

Text2Tracks: Prompt-based Music Recommendation via Generative Retrieval

Enrico Palumbo, Gustavo Penha, Andreas Damianou, José Luis Redondo García, Timothy Christopher Heath, Alice Wang, Hugues Bouchard, Mounia Lalmas

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

Multi-Task Learning for Extracting Menstrual Characteristics from Clinical Notes

Anna Shopova, Cristoph Lippert, Leslee J. Shaw, Eugenia Alleva

专题命中 检索器与排序 ：hybrid retrieval(abstract)；分类 cs.CL

A Retrieval-Augmented Knowledge Mining Method with Deep Thinking LLMs for Biomedical Research and Clinical Support

Yichun Feng, Jiawei Wang, Ruikun He, Lu Zhou, Yixue Li

专题命中 检索器与排序 ：knowledge retrieval(abstract)；分类 cs.CL

Multi-Task Semantic Communications via Large Models

Wanli Ni, Zhijin Qin, Haofeng Sun, Xiaoming Tao, Zhu Han

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

Comments 7 pages, 6 figures

Motif Counting in Complex Networks: A Comprehensive Survey

Haozhe Yin, Kai Wang, Wenjie Zhang, Yizhang He, Ying Zhang, Xuemin Lin

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

Dense Passage Retrieval in Conversational Search

Ahmed H. Salamah, Pierre McWhannel, Nicole Yan

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

TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

Shanghua Gao, Richard Zhu, Zhenglun Kong, Ayush Noori, Xiaorui Su, Curtis Ginder, Theodoros Tsiligkaridis, Marinka Zitnik

专题命中 检索器与排序 ：knowledge retrieval(abstract)；分类 cs.AI

Comments Project page: https://zitniklab.hms.harvard.edu/TxAgent TxAgent code: https://github.com/mims-harvard/TxAgent ToolUniverse code: https://github.com/mims-harvard/ToolUniverse