语言大模型 / LLM

Large Language Models for Software Testing Education: an Experience Report

大型语言模型在软件测试教育中的应用：经验报告

Peng Yang, Yunfeng Zhu, Chao Chang, Shengcheng Yu, Zhenyu Chen, Yong Tang

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；prompting(abstract)

AI总结 本文通过混合方法研究，探讨学生在使用LLM进行测试任务时的交互问题及教学策略，提出轻量级提示框架以提升测试脚本生成能力。

Comments Paper Accepted by the ACM International Conference on the Foundations of Software Engineering (FSE 2026) Software Engineering Education Track

DiffVP: Differential Visual Semantic Prompting for LLM-Based CT Report Generation

DiffVP：基于LLM的CT报告生成的微分视觉语义提示

Yuhe Tian, Kun Zhang, Haoran Ma, Rui Yan, Yingtai Li, Rongsheng Wang, Shaohua Kevin Zhou

机构 * Department of Electronic Engineering ； Information Science, School of Information Science ； Technology, University of Science ； Technology of China (USTC), Hefei, Anhui 230026, China School of Biomedical Engineering, Division of Life Sciences ； Medicine, University of Science ； Technology of China (USTC), Hefei, Anhui 230026, China Center for Medical Imaging, Robotics, Analytic Computing \& Learning (MIRACLE), Suzhou Institute for Advanced Research, University of Science ； Technology of China (USTC), Suzhou, Jiangsu 215123, China Jiangsu Provincial Key Laboratory of Multimodal Digital Twin Technology, University of Science ； Technology of China (USTC), Suzhou, Jiangsu 215123, China State Key Laboratory of Precision ； Intelligent Chemistry, University of Science 纠错

专题命中 领域大模型 ：LLM(title,abstract)；prompting(title,abstract)；large language model(abstract)；language model(abstract)

AI总结 DiffVP通过微分视觉提示方法，利用扫描与参考之间的高阶语义差异指导LLM生成CT报告，提升报告准确性，实验表明其在BLEU和临床效果上均优于现有方法。

Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages

小型语言模型在低资源语言中隐私保护的临床信息提取

Mohammadreza Ghaffarzadeh-Esfahani, Nahid Yousefian, Ebrahim Heidari-Farsani, Ali Akbar Omidvarian, Sepehr Ghahraei, Atena Farangi, AmirBahador Boroumand

机构 * Student Research Committee Isfahan University of Medical Sciences（伊斯法罕医学科学大学学生研究委员会） ； Department of Emergency Medicine Isfahan University of Medical Sciences（伊斯法罕医学科学大学急诊医学科） 纠错

专题命中 领域大模型 ：language model(title,abstract)；small language model(title,abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本文提出利用小型语言模型结合翻译模型，实现低资源语言中隐私保护的临床信息提取，验证了模型规模和输入语言策略联合优化的重要性。

Comments 16 pages, 3 figures, 2 supplementary files

Gender and Race Bias in Consumer Product Recommendations by Large Language Models

大型语言模型在消费者产品推荐中的性别和种族偏见

Ke Xu, Shera Potka, Alex Thomo

机构 * University of Victoria, British Columbia, Canada（维多利亚大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本文研究了大型语言模型在消费者产品推荐中存在性别和种族偏见的问题，通过提示工程和三种分析方法揭示了推荐中的不平等现象，并强调了构建更公平推荐系统的重要性。

Comments Accepted at the 39th International Conference on Advanced Information Networking and Applications (AINA 2025)

Journal ref Lecture Notes in Networks and Systems, vol 1210, pp. 222-233, 2025

Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models

在临床访谈中检测PTSD：自然语言处理方法和大语言模型的比较分析

Feng Chen, Dror Ben-Zeev, Gillian Sparks, Arya Kadakia, Trevor Cohen

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本研究比较了NLP方法和大语言模型在临床访谈中检测PTSD的效果，发现领域特定模型和嵌入方法表现最佳，强调了领域适应技术在PTSD筛查中的潜力。

Leveraging Machine Learning and Large Language Models for Automated Image Clustering and Description in Legal Discovery

利用机器学习和大语言模型实现法律发现中的自动化图像聚类与描述

Qiang Mao, Fusheng Wei, Robert Neary, Charles Wang, Han Qin, Jianping Zhang, Nathaniel Huber-Fliflet

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；prompting(abstract)

AI总结 本文提出利用机器学习和大语言模型实现法律发现中自动化图像聚类与描述，通过比较不同采样策略、提示技术和生成方法，提升大规模图像数据处理的效率和准确性。

Swarms of Large Language Model Agents for Protein Sequence Design with Experimental Validation

大规模语言模型代理群组用于蛋白质序列设计的实验验证

Fiona Y. Wang, Di Sheng Lee, David L. Kaplan, Markus J. Buehler

机构 * Laboratory for Atomistic and Molecular Mechanics (LAMM), Department of Biological Engineering, Massachusetts Institute of Technology（原子分子力学实验室（LAMM），生物工程系，麻省理工学院） ； Department of Biomedical Engineering, Tufts University（生物医学工程系，塔夫茨大学） ； Laboratory for Atomistic and Molecular Mechanics (LAMM), Department of Civil and Environmental Engineering, Department of Mechanical Engineering, Center for Computational Science and Engineering, Schwarzman College of Computing, Massachusetts Institute of Technology（原子分子力学实验室（LAMM），土木与环境工程系，机械工程系，计算科学与工程中心，计算机科学学院，麻省理工学院） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本文提出了一种基于大规模语言模型代理群组的蛋白质序列设计方法，通过去中心化协调实现高效目标导向设计，无需微调或特定训练，且在实验中验证了其有效性。

LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation

LLMInit: 从大型语言模型中获得免费午餐：用于推荐系统选择性初始化

Weizhi Zhang, Liangwei Yang, Wooseong Yang, Henry Peng Zou, Yuqing Liu, Ke Xu, Sourav Medya, Philip S. Yu

机构 * University of Illinois Chicago（伊利诺伊大学芝加哥分校） ； Salesforce AI Research（Salesforce AI研究） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 LLMInit通过选择性初始化策略将预训练LLM嵌入整合到协同过滤模型中，提升推荐性能并降低计算成本。

Comments Accepted in EMNLP 2025 Industry Track

QwenCLIP: Boosting Medical Vision-Language Pretraining via LLM Embeddings and Prompt tuning

Xiaoyang Wei, Camille Kurtz, Florence Cloppet

机构 * Laboratoire d'Informatique Paris Descartes (LIPADE), Université Paris Cité (France)（巴黎笛卡尔大学信息学实验室（LIPADE），巴黎城市大学（法国）） 纠错

专题命中 领域大模型 ：LLM(title,abstract)；pretraining(title,abstract)；large language model(abstract)；language model(abstract)

Comments This work has been submitted to the IEEE ISBI for possible publication

MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses

Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, Dongzhan Zhou

机构 * Nanyang Technological University（南洋理工大学） ； Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； University of Science and Technology of China（中国科学技术大学） ； Wuhan University（武汉大学） ； University of New South Wales（新南威尔士大学） ； GreenDynamics ； Singapore University of Technology and Design（新加坡科技设计大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted by ICLR 2025

Evaluating the Limits of Large Language Models in Multilingual Legal Reasoning

Antreas Ioannou, Andreas Shiamishis, Nora Hollenstein, Nezihe Merve Gürel

机构 * Delft University of Technology（代尔夫特理工大学） ； University of Zurich（苏黎世大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 39 pages, 36 figures. Code and evaluation pipeline available at https://github.com/RobustML-Lab/Legal-Multilingual-Evaluation-of-LLMs

Leveraging Large Language Models to Effectively Generate Visual Data for Canine Musculoskeletal Diagnoses

Martin Thißen, Thi Ngoc Diep Tran, Barbara Esteve Ratsch, Ben Joel Schönbein, Ute Trapp, Beate Egner, Romana Piat, Elke Hergenröther

机构 * Darmstadt University of Applied Sciences（达姆施塔特应用技术大学） ； Veterinary Academy of Higher Learning（兽医高等学习学院） ； European University of Technology（欧洲技术大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；prompting(abstract)

Journal ref Computer Science Research Notes 3501(1) (2025) 27-38

Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks

Julian Junyan Wang, Victor Xiaoqi Wang

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 76 pages, 20 tables, 12 figures

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression

Wei Huang, Huang Wei, Yinggui Wang

机构 * Ant Group, China（蚂蚁集团） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted by EMNLP 2025

The language of time: a language model perspective on time-series foundation models

Yi Xie, Yun Xiong, Zejian Shi, Hao Niu, Zhengfu Liu

机构 * College of Computer Science and Artificial Intelligence, Fudan University（计算机科学与人工智能学院，复旦大学） ； Shanghai Key Laboratory of Data Science（上海数据科学重点实验室） ； ZCTech ； School of Mathematics and Statistics, Beijing Institute of Technology（数学与统计学学院，北京理工大学） 纠错

专题命中 领域大模型 ：language model(title,abstract)；foundation model(title,abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

SequentialBreak: Large Language Models Can be Fooled by Embedding Jailbreak Prompts into Sequential Prompt Chains

Bijoy Ahmed Saiem, MD Sadik Hossain Shanto, Rakib Ahsan, Md Rafi ur Rashid

机构 * Bangladesh University of Engineering and Technology（孟加拉工程科技大学） ； Pennsylvania State University（宾夕法尼亚州立大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation

Hanyin Wang, Chufan Gao, Bolun Liu, Qiping Xu, Guleid Hussein, Mohamad El Labban, Kingsley Iheasirim, Hariprasad Korsapati, Chuck Outcalt, Jimeng Sun

机构 * Mayo Clinic Health System（梅奥诊所健康系统） ； School of Computing and Data Science, UIUC（UIUC计算与数据科学学院） ； Mayo Clinic Rochester（梅奥诊所罗切斯特分部） ； Carle Illinois College of Medicine, UIUC（UIUC卡勒伊利诺伊医学院） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

KERL: Knowledge-Enhanced Personalized Recipe Recommendation using Large Language Models

Fnu Mohbat, Mohammed J Zaki

机构 * Rensselaer Polytechnic Institute（拉特格斯理工学院） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted at ACL 2025

MEG: Medical Knowledge-Augmented Large Language Models for Question Answering

Laura Cabello, Carmen Martin-Turrero, Uchenna Akujuobi, Anders Søgaard, Carlos Bobed

机构 * University of Copenhagen（哥本哈根大学） ； Sony AI（索尼人工智能） ； University of Zaragoza（阿拉维萨大学） 纠错

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Diabetica: Adapting Large Language Model to Enhance Multiple Medical Tasks in Diabetes Care and Management

Lai Wei, Zhen Ying, Muyang He, Yutong Chen, Qian Yang, Yanzhe Hong, Jiaping Lu, Kaipeng Zheng, Shaoting Zhang, Xiaoying Li, Weiran Huang, Ying Chen

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted by ICLR 2025 SCI-FM workshop

ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

Zixiang Wang, Yinghao Zhu, Huiya Zhao, Xiaochen Zheng, Dehao Sui, Tianlong Wang, Wen Tang, Yasha Wang, Ewen Harrison, Chengwei Pan, Junyi Gao, Liantao Ma

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ACM TheWebConf 2025 Conference (WWW 2025) Research Track

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains

Ran Xu, Hui Liu, Sreyashi Nag, Zhenwei Dai, Yaochen Xie, Xianfeng Tang, Chen Luo, Yang Li, Joyce C. Ho, Carl Yang, Qi He

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to NAACL 2025 main conference

Journal ref NAACL 2025

Large language models as oracles for instantiating ontologies with domain-specific knowledge

Giovanni Ciatto, Andrea Agiollo, Matteo Magnini, Andrea Omicini

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Journal ref Knowledge-Based Systems 310 (2025) 112940

Multi-Objective Large Language Model Unlearning

Zibin Pan, Shuwen Zhang, Yuesheng Zheng, Chi Li, Yuheng Cheng, Junhua Zhao

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments To be published in the Proceedings of 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-2025)

Hypothesis Generation with Large Language Models

Yangqiaoyu Zhou, Haokun Liu, Tejes Srivastava, Hongyuan Mei, Chenhao Tan

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 28 pages, 6 figures, code link: https://github.com/ChicagoHAI/hypothesis_generation. Accepted by the 1st Workshop on NLP for Science (NLP4Science) at EMNLP 2024

Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification

Filippos Gouidis, Katerina Papantoniou, Konstantinos Papoutsakis, Theodore Patkos, Antonis Argyros, Dimitris Plexousakis

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted at the AAAI-MAKE 2024

Journal ref Proceedings of the AAAI Spring Symposium, 2024, pages 115-124

CovidLLM: A Robust Large Language Model with Missing Value Adaptation and Multi-Objective Learning Strategy for Predicting Disease Severity and Clinical Outcomes in COVID-19 Patients

Shengjun Zhu, Siyu Liu, Yang Li, Qing Lei, Hongyan Hou, Hewei Jiang, Shujuan Guo, Feng Wang, Rongshang Chen, Xionglin Fan, Shengce Tao, Jiaxin Cai

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review

Rui Ye, Xianghe Pang, Jingyi Chai, Jiaao Chen, Zhenfei Yin, Zhen Xiang, Xiaowen Dong, Jing Shao, Siheng Chen

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 27 pages, 24 figures

Large Language Model Supply Chain: A Research Agenda

Shenao Wang, Yanjie Zhao, Xinyi Hou, Haoyu Wang

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；foundation model(abstract)

Comments Accepted by ACM Transactions on Software Engineering and Methodology (TOSEM) Special Issue: 2030 Software Engineering Roadmap

A Review of Large Language Models and Autonomous Agents in Chemistry

Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White

专题命中 领域大模型 ：large language model(title,abstract)；language model(title,abstract)；LLM(abstract)；分类 cs.CL、cs.AI、cs.LG