RAG / 检索增强生成

MetaGen Blended RAG: Unlocking Zero-Shot Precision for Specialized Domain Question-Answering

Kunal Sawarkar, Shivam R. Solanki, Abhilasha Mangal

机构 * IBM 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

Can Large Language Models Identify Materials from Radar Signals?

Jiangyou Zhu, Hongyu Deng, He Chen

机构 * The Chinese University of Hong Kong（香港中文大学） 纠错

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

PyLate: Flexible Training and Retrieval for Late Interaction Models

Antoine Chaffin, Raphaël Sourty

机构 * LightOn Nancy France（LightOn Nancy） ； LightOn Paris France（LightOn Paris） 纠错

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

Comments 5 pages

Pay What LLM Wants: Can LLM Simulate Economics Experiment with 522 Real-human Persona?

Junhyuk Choi, Hyeonchu Park, Haemin Lee, Hyebeen Shin, Hyun Joung Jin, Bugeun Kim

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

Comments Preprint

Agent Lightning: Train ANY AI Agents with Reinforcement Learning

Xufang Luo, Yuge Zhang, Zhiyuan He, Zilong Wang, Siyun Zhao, Dongsheng Li, Luna K. Qiu, Yuqing Yang

机构 * Microsoft Research（微软研究院） 纠错

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

GUI-ReRank: Enhancing GUI Retrieval with Multi-Modal LLM-based Reranking

Kristian Kolthoff, Felix Kretzer, Christian Bartelt, Alexander Maedche, Simone Paolo Ponzetto

专题命中 检索器与排序 ：RAG(abstract)

Token-Level Precise Attack on RAG: Searching for the Best Alternatives to Mislead Generation

Zizhong Li, Haopeng Zhang, Jiawei Zhang

机构 * University of California, Davis（加州大学戴维斯分校） ； University of Hawaii at Mānoa（夏威夷大学马诺阿分校） 纠错

专题命中 知识库问答 ：RAG(title,abstract)；retrieval-augmented generation(abstract)；retriever(abstract)；分类 cs.CL

CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation

Kaiwen Zhao, Bharathan Balaji, Stephen Lee

机构 * University of Pittsburgh（匹兹堡大学） ； Amazon（亚马逊） 纠错

专题命中 知识库问答 ：retrieval-augmented generation(title)；RAG(title)；分类 cs.CL、cs.AI

Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?

Wenxuan Shen, Mingjia Wang, Yaochen Wang, Dongping Chen, Junjie Yang, Yao Wan, Weiwei Lin

机构 * South China University of Technology（华南理工大学） ； Huazhong University of Science and Technology（华中科技大学） ； University of Maryland（马里兰大学） 纠错

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

Comments In submission. Project website: https://double-bench.github.io/

The Multi-Round Diagnostic RAG Framework for Emulating Clinical Reasoning

Penglei Sun, Yixiang Chen, Xiang Li, Xiaowen Chu

机构 * The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）） 纠错

专题命中 图谱与结构化RAG ：RAG(title,abstract)；retrieval-augmented generation(abstract)；分类 cs.CL

Tackling Distribution Shift in LLM via KILO: Knowledge-Instructed Learning for Continual Adaptation

Iing Muttakhiroh, Thomas Fevens

机构 * Concordia University（康科迪亚大学） 纠错

专题命中 图谱与结构化RAG ：knowledge retrieval(abstract)；分类 cs.CL

SAGE-HLS: Syntax-Aware AST-Guided LLM for High-Level Synthesis Code Generation

M Zafir Sadik Khan, Nowfel Mashnoor, Mohammad Akyash, Kimia Azar, Hadi Kamali

专题命中 RAG评测 ：retrieval-augmented generation(abstract)；RAG(abstract)

Comments Accepted to the IEEE International Conference on Computer Design (ICCD 2025)

Key-Augmented Neural Triggers for Knowledge Sharing

Alex Wolf, Marco Edoardo Palma, Pooja Rani, Harald C. Gall

专题命中 RAG评测 ：RAG(abstract)

MRG-Bench: Evaluating and Exploring the Requirements of Context for Repository-Level Code Generation

Haiyang Li

专题命中 RAG评测 ：RAG(abstract)