RAG / 检索增强生成

Query-driven Document-level Scientific Evidence Extraction from Biomedical Studies

Massimiliano Pronesti, Joao Bettencourt-Silva, Paul Flanagan, Alessandra Pascale, Oisin Redmond, Anya Belz, Yufang Hou

机构 * First Author Affiliation（第一作者机构） ； Second Author Affiliation（第二作者机构） 纠错

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

Comments Accepted at ACL 2025 Main Conference

GeAR: Generation Augmented Retrieval

Haoyu Liu, Shaohan Huang, Jianfeng Liu, Yuefeng Zhan, Hao Sun, Weiwei Deng, Feng Sun, Furu Wei, Qi Zhang

机构 * Microsoft Corporation（微软公司） 纠错

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

Comments In ACL 2025

Controllable Context Sensitivity and the Knob Behind It

Julian Minder, Kevin Du, Niklas Stoehr, Giovanni Monea, Chris Wendler, Robert West, Ryan Cotterell

机构 * ETH Zürich（苏黎世联邦理工学院） ； EPFL（苏黎世联邦理工学院） ； Cornell University（康奈尔大学） 纠错

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

Comments Published as a conference paper at ICLR 2025

ARise: Towards Knowledge-Augmented Reasoning via Risk-Adaptive Search

Yize Zhang, Tianshu Wang, Sirui Chen, Kun Wang, Xingyu Zeng, Hongyu Lin, Xianpei Han, Le Sun, Chaochao Lu

机构 * Shanghai AI Laboratory（上海人工智能实验室） ； Shanghai Innovation Institute（上海创新研究院） ； Shanghai Jiao Tong University（上海交通大学） ； SenseTime（商汤科技） ； Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所） ； Tongji University（同济大学） ； Hangzhou Institute for Advanced Study（杭州高等研究院） ； University of Chinese Academy of Sciences（中国科学院大学） 纠错

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

Comments Accepted to ACL 2025 Main. Project homepage: https://opencausalab.github.io/ARise

DailyQA: A Benchmark to Evaluate Web Retrieval Augmented LLMs Based on Capturing Real-World Changes

Jiehan Cheng, Zhicheng Dou

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

Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds

Gaël Gendron, Jože M. Rožanec, Michael Witbrock, Gillian Dobbie

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

Comments 29 pages, 9 pages for the main paper, 20 pages for the references and appendix, 25 figures

Exploring new Approaches for Information Retrieval through Natural Language Processing

Manak Raj, Nidhi Mishra

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

Comments 12 pages, 4 figures, comprehensive literature review covering six key IR-NLP papers, plus keywords and full reference list

Memorization and Knowledge Injection in Gated LLMs

Xu Pan, Ely Hahami, Zechen Zhang, Haim Sompolinsky

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

A model and package for German ColBERT

Thuong Dang, Qiqi Chen

机构 * Thuong Dang, Qiqi Chen（独立研究者） 纠错

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

Multi-Field Adaptive Retrieval

Millicent Li, Tongfei Chen, Benjamin Van Durme, Patrick Xia

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

Comments ICLR 2025, Spotlight

Patience is all you need! An agentic system for performing scientific literature review

David Brett, Anniek Myatt

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

Comments 10 pages, 5 figures

Role of Databases in GenAI Applications

Santosh Bhupathi

专题命中 检索器与排序 ：vector search(abstract)；分类 cs.AI、cs.DB

LLM4Ranking: An Easy-to-use Framework of Utilizing Large Language Models for Document Reranking

Qi Liu, Haozhe Duan, Yiqun Chen, Quanfeng Lu, Weiwei Sun, Jiaxin Mao

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

TempRetriever: Fusion-based Temporal Dense Passage Retrieval for Time-Sensitive Questions

Abdelrahman Abdallah, Bhawna Piryani, Jonas Wallat, Avishek Anand, Adam Jatowt

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

GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Xin Zhang, Yanzhao Zhang, Wen Xie, Mingxin Li, Ziqi Dai, Dingkun Long, Pengjun Xie, Meishan Zhang, Wenjie Li, Min Zhang

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

Comments Accepted to CVPR 2025, models at https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct

RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models

Haoran Hao, Jiaming Han, Changsheng Li, Yu-Feng Li, Xiangyu Yue

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

Comments Accepted by CVPR 2025. Code: https://github.com/Hoar012/RAP-MLLM

OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment

Hamed Babaei Giglou, Jennifer D'Souza, Oliver Karras, Sören Auer

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

Comments 18 pages, 3 figures. Accepted for the ESWC 2025 Resource Track

Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models

Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, Gustavo Alonso

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

Comments Accepted by VLDB 2025

Bootstrap Your Own Context Length

Liang Wang, Nan Yang, Xingxing Zhang, Xiaolong Huang, Furu Wei

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

Comments 19 pages

AI-native Memory 2.0: Second Me

Jiale Wei, Xiang Ying, Tao Gao, Fangyi Bao, Felix Tao, Jingbo Shang

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

Unlocking Legal Knowledge with Multi-Layered Embedding-Based Retrieval

João Alberto de Oliveira Lima

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

Comments 27 pages, 10 figures

Journal ref Artificial Intelligence in Legislative Services: Principles for Effective Implementation. 2024

Delusions of Large Language Models

Hongshen Xu, Zixv yang, Zichen Zhu, Kunyao Lan, Zihan Wang, Mengyue Wu, Ziwei Ji, Lu Chen, Pascale Fung, Kai Yu

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

IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval

Tingyu Song, Guo Gan, Mingsheng Shang, Yilun Zhao

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

Comments NAACL 2025 Main

Evaluating Search Engines and Large Language Models for Answering Health Questions

Marcos Fernández-Pichel, Juan C. Pichel, David E. Losada

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

Rethinking Data: Towards Better Performing Domain-Specific Small Language Models

Boris Nazarov, Darya Frolova, Yackov Lubarsky, Alexei Gaissinski, Pavel Kisilev

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

Journal ref IEEE Global Communications Conference, GLOBECOM 2024 Workshop IMMLLM6G

CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking

Tarun Suresh, Revanth Gangi Reddy, Yifei Xu, Zach Nussbaum, Andriy Mulyar, Brandon Duderstadt, Heng Ji

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

Comments Published as a conference paper at ICLR 2025. First and second author had equal contribution

RAMIE: Retrieval-Augmented Multi-task Information Extraction with Large Language Models on Dietary Supplements

Zaifu Zhan, Shuang Zhou, Mingchen Li, Rui Zhang

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

Journal ref Journal of the American Medical Informatics Association, Volume 32, Issue 3, March 2025, Pages 545:554

Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers

Shijie Chen, Bernal Jiménez Gutiérrez, Yu Su

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

Comments ICLR 2025

The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve?

Zhenheng Tang, Xiang Liu, Qian Wang, Peijie Dong, Bingsheng He, Xiaowen Chu, Bo Li

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

R$^3$Mem: Bridging Memory Retention and Retrieval via Reversible Compression

Xiaoqiang Wang, Suyuchen Wang, Yun Zhu, Bang Liu

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

Comments Work in progress