RAG / 检索增强生成

Can Language Models Replace Programmers for Coding? REPOCOD Says 'Not Yet'

Shanchao Liang, Yiran Hu, Nan Jiang, Lin Tan

机构 * Purdue University（普渡大学） 纠错

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

Dr. GPT Will See You Now, but Should It? Exploring the Benefits and Harms of Large Language Models in Medical Diagnosis using Crowdsourced Clinical Cases

Bonam Mingole, Aditya Majumdar, Firdaus Ahmed Choudhury, Jennifer L. Kraschnewski, Shyam S. Sundar, Amulya Yadav

专题命中 RAG评测 ：RAG(abstract)；分类 cs.AI

LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning

Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Wei Ma, Lyuye Zhang, Yang Liu, Yingjiu Li

机构 * Nanyang Technological University, Singapore（南洋理工大学） ； The Hong Kong University of Science（香港科学与技术大学） ； MetaTrust Labs（MetaTrust实验室） ； Singapore Management University, Singapore（新加坡管理学院） ； University of Oregon, Eugene, OR, USA（俄勒冈大学） 纠错

专题命中 RAG评测 ：knowledge retrieval(abstract)；分类 cs.AI

Comments This is a technical report by Nanyang Technological University. Updated to support Solidity, Java and C/C++

Improving Factuality with Explicit Working Memory

Mingda Chen, Yang Li, Karthik Padthe, Rulin Shao, Alicia Sun, Luke Zettlemoyer, Gargi Ghosh, Wen-tau Yih

机构 * Meta FAIR 纠错

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Comments ACL 2025 Camera Ready

Multi-modal Retrieval Augmented Multi-modal Generation: Datasets, Evaluation Metrics and Strong Baselines

Zi-Ao Ma, Tian Lan, Rong-Cheng Tu, Yong Hu, Yu-Shi Zhu, Tong Zhang, Heyan Huang, Zhijing Wu, Xian-Ling Mao

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Transparentize the Internal and External Knowledge Utilization in LLMs with Trustworthy Citation

Jiajun Shen, Tong Zhou, Yubo Chen, Delai Qiu, Shengping Liu, Kang Liu, Jun Zhao

机构 * The Key Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of Automation, Chinese Academy of Sciences（认知与决策智能复杂系统重点实验室，中国科学院自动化研究所） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； University of Chinese Academy of Sciences（中国科学院大学） ； Unisound Al Technology Co,Ltd（Unisound人工智能技术有限公司） ； Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） 纠错

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

Comments 19 pages, 14 figures

Can LLMs reason over extended multilingual contexts? Towards long-context evaluation beyond retrieval and haystacks

Amey Hengle, Prasoon Bajpai, Soham Dan, Tanmoy Chakraborty

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

Comments 33 Pages in Total - 23 (Main Manuscript) + 10 (Appendix)

KnowsLM: A framework for evaluation of small language models for knowledge augmentation and humanised conversations

Chitranshu Harbola, Anupam Purwar

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Loss Functions and Metrics in Deep Learning

Juan Terven, Diana M. Cordova-Esparza, Alfonso Ramirez-Pedraza, Edgar A. Chavez-Urbiola, Julio A. Romero-Gonzalez

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

Comments 134 pages, 4 figures, 21 tables, 238 equations

Journal ref Terven, J., Cordova-Esparza, DM., Romero-González, JA. et al. A comprehensive survey of loss functions and metrics in deep learning. Artif Intell Rev 58, 195 (2025)

ModiGen: A Large Language Model-Based Workflow for Multi-Task Modelica Code Generation

Jiahui Xiang, Tong Ye, Peiyu Liu, Yinan Zhang, Wenhai Wang

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

Command R7B Arabic: A Small, Enterprise Focused, Multilingual, and Culturally Aware Arabic LLM

Yazeed Alnumay, Alexandre Barbet, Anna Bialas, William Darling, Shaan Desai, Joan Devassy, Kyle Duffy, Stephanie Howe, Olivia Lasche, Justin Lee, Anirudh Shrinivason, Jennifer Tracey

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

From "Hallucination" to "Suture": Insights from Language Philosophy to Enhance Large Language Models

Qiantong Wang

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Comments 7 pages

Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution

Kun Li, Tianhua Zhang, Yunxiang Li, Hongyin Luo, Abdalla Moustafa, Xixin Wu, James Glass, Helen Meng

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

Agentic Mixture-of-Workflows for Multi-Modal Chemical Search

Tiffany J. Callahan, Nathaniel H. Park, Sara Capponi

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

Comments PDF includes supplemental material

Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics

Shuqi Yang, Mingrui Jing, Shuai Wang, Jiaxin Kou, Manfei Shi, Weijie Xing, Yan Hu, Zheng Zhu

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

Comments 45 pages, 1 figure, 5 tables

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding

Xinyu Yang, Tianqi Chen, Beidi Chen

专题命中 RAG评测 ：RAG(abstract)；分类 cs.AI

Comments ICLR 2025

WIKIGENBENCH: Exploring Full-length Wikipedia Generation under Real-World Scenario

Jiebin Zhang, Eugene J. Yu, Qinyu Chen, Chenhao Xiong, Dawei Zhu, Han Qian, Mingbo Song, Weimin Xiong, Xiaoguang Li, Qun Liu, Sujian Li

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Comments COLING 2025 Camera Ready

MST-R: Multi-Stage Tuning for Retrieval Systems and Metric Evaluation

Yash Malviya, Karan Dhingra, Maneesh Singh

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

FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documents

Yilun Zhao, Yitao Long, Yuru Jiang, Chengye Wang, Weiyuan Chen, Hongjun Liu, Yiming Zhang, Xiangru Tang, Chen Zhao, Arman Cohan

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Comments EMNLP 2024

Enhancing LLM's Cognition via Structurization

Kai Liu, Zhihang Fu, Chao Chen, Wei Zhang, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, Jieping Ye

专题命中 RAG评测 ：dense retrieval(abstract)；分类 cs.CL

Comments This paper has been accepted by NeurIPS 2024. Code is available at https://github.com/alibaba/struxgpt

Attribute or Abstain: Large Language Models as Long Document Assistants

Jan Buchmann, Xiao Liu, Iryna Gurevych

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Comments Accepted at EMNLP 2024. Code and data: https://github.com/UKPLab/arxiv2024-attribute-or-abstain

L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?

Zecheng Tang, Keyan Zhou, Juntao Li, Baibei Ji, Jianye Hou, Min Zhang

专题命中 RAG评测 ：RAG(abstract)；分类 cs.CL

Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data

Felix J. Dorfner, Amin Dada, Felix Busch, Marcus R. Makowski, Tianyu Han, Daniel Truhn, Jens Kleesiek, Madhumita Sushil, Jacqueline Lammert, Lisa C. Adams, Keno K. Bressem

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

Comments 10 pages, 3 tables, 1 figure

Large Language Models Reflect Human Citation Patterns with a Heightened Citation Bias

Andres Algaba, Carmen Mazijn, Vincent Holst, Floriano Tori, Sylvia Wenmackers, Vincent Ginis

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

Comments 30 pages, 13 figures, 4 tables. Added GPT-4o and Claude 3.5 results

Retrieve, Generate, Evaluate: A Case Study for Medical Paraphrases Generation with Small Language Models

Ioana Buhnila, Aman Sinha, Mathieu Constant

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

Comments KnowledgeableLM 2024

SlicerChat: Building a Local Chatbot for 3D Slicer

Colton Barr

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

Design and evaluation of AI copilots -- case studies of retail copilot templates

Michal Furmakiewicz, Chang Liu, Angus Taylor, Ilya Venger

专题命中 RAG评测 ：knowledge retrieval(abstract)；分类 cs.AI

Comments 22 pages, 4 figures

UMBRELA: UMbrela is the (Open-Source Reproduction of the) Bing RELevance Assessor

Shivani Upadhyay, Ronak Pradeep, Nandan Thakur, Nick Craswell, Jimmy Lin

专题命中 RAG评测 ：RAG(abstract)；分类 cs.IR

Comments 5 pages, 3 figures

AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls

Yu Du, Fangyun Wei, Hongyang Zhang

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

On Elastic Language Models

Chen Zhang, Benyou Wang, Dawei Song

专题命中 RAG评测 ：dense retrieval(abstract)；分类 cs.IR

Comments 27 pages, 11 figures, 9 tables