语言大模型 / LLM

Securing the Dark Matter: A Semantic-Enhanced Neuro-Symbolic Framework for Supply Chain Analysis of Opaque Industrial Software

守护暗物质：一种语义增强的神经符号框架用于opaque工业软件的供应链分析

Bowei Ning, Xuejun Zong, Lian Lian, Kan He, Yifei Sun, Yuxiang Lei, Plamen Vasilev

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

AI总结 本文提出一种语义增强的神经符号框架，通过直接从opaque二进制中重建行为语义，实现可扩展的全局风险推理，提升供应链分析的准确性和语义映射精度。

Comments 33 pages, 13 figures

ViLegalNLI: Natural Language Inference for Vietnamese Legal Texts

ViLegalNLI：越南法律文本的自然语言推理

Nhung Thi-Hong Duong, Mai Ngoc Ho, Tin Van Huynh, Kiet Van Nguyen

机构 * University of Information Technology（信息技术大学） ； Vietnam National University（越南国家大学） 纠错

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

AI总结 本文提出ViLegalNLI，首个针对法律领域构建的越南语自然语言推理数据集，包含42,012个前提-假设对，涵盖多种法律领域，用于评估法律推理的结构逻辑与术语一致性。

Comments 33 pages, 17 figures

Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain

学习隐藏风险：面向金融领域的可控多轮红队测试框架

Gang Cheng, Haibo Jin, Wenbin Zhang, Haohan Wang, Jun Zhuang

机构 * Bloomberg（彭博社） ； University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； Florida International University（佛罗里达国际大学） ； Boise State University（博伊西州立大学） 纠错

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

AI总结 本文提出CoRT框架，通过可控的多轮红队测试方法，针对金融领域潜在风险进行隐蔽攻击，提升LLM在监管合规方面的安全性。

Comments Accepted for ACL'26 (Main). TL;DR: We propose a controllable multi-turn risk-concealed red-teaming framework, CoRT, that progressively conceals surface-level risk while exploiting regulatory-violating behaviors on a proposed new benchmark, FinRisk-Bench

Code for All: Educational Applications of the "Vibe Coding" Hackathon in Programming Education across All Skill Levels

面向所有人的代码：Vibe Coding黑客松在编程教育中的应用

Ashley J. Chen, Yijia Cao, Minghao Shao, Ramesh Karri, Muhammad Shafique

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

AI总结 本文通过为期一个月的在线黑客松活动，探讨了Vibe Coding在不同技能水平编程教育中的教育价值，评估了AI生成代码对学习效果和项目质量的影响。

Comments 15 pages, 14 figures

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

MedProbeBench: 在深度证据整合中的系统性基准测试用于专家级医疗指南

Jiyao Liu, Jianghan Shen, Sida Song, Tianbin Li, Xiaojia Liu, Rongbin Li, Ziyan Huang, Jiashi Lin, Junzhi Ning, Changkai Ji, Siqi Luo, Wenjie Li, Chenglong Ma, Ming Hu, Jing Xiong, Jin Ye, Bin Fu, Ningsheng Xu, Yirong Chen, Lei Jin, Hong Chen, Junjun He

机构 * Fudan University（复旦大学） ； Nanjing University（南京大学） ； Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； University of Hong Kong（香港大学） 纠错

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

AI总结 本文提出MedProbeBench，首个利用高质量临床指南作为专家级参考的基准，通过1200+任务自适应评估标准和5130+原子性声明验证，评估17种LLM和深度研究代理在证据整合和指南生成中的能力差距。

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

什么使AI研究可重复？可执行知识图谱作为科学知识表示

Yujie Luo, Zhuoyun Yu, Xuehai Wang, Yuqi Zhu, Ningyu Zhang, Lanning Wei, Lun Du, Da Zheng, Huajun Chen

机构 * Zhejiang University（浙江大学） ； Ant Group（蚂蚁集团） ； Zhejiang University - Ant Group Joint Laboratory of Knowledge Graph（知识图谱联合实验室） 纠错

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

AI总结 本文提出可执行知识图谱(xKG)，通过整合文献中的代码片段和技术洞察，提升AI研究的可重复性，实验显示其在PaperBench上性能提升显著。

Comments ACL 2026

Bridging the Interpretation Gap in Accessibility Testing: Empathetic and Legal-Aware Bug Report Generation via Large Language Models

弥合可访问性测试中的解释鸿沟：通过大语言模型生成共情且法律意识的缺陷报告

Ryoya Koyama, Zhiyao Wang, Devi Karolita, Jialong Li, Kenji Tei

专题命中 领域大模型 ：large language model(title)；language model(title)

AI总结 本文提出HEAR框架，通过语义切片和视觉定位重建UI上下文，注入残疾导向的人设并多层推理，生成共情且法律意识的缺陷报告，提升非专业人士对用户伤害和合规风险的认知。

SciNav: A General Agent Framework for Scientific Coding Tasks

SciNav：一种通用的科学编码任务代理框架

Tianshu Zhang, Huan Sun

机构 * The Ohio State University（俄亥俄州立大学） 纠错

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

AI总结 本文提出SciNav框架，用于科学编码任务，通过相对判断指导的top-K搜索提升解决方案探索效率，优于直接提示和现有代理。

Comments Accepted by ICLR 2026

LLMDR: Large language model driven framework for missing data recovery in mixed data under low resource regime

LLMDR：基于大型语言模型的混合数据在低资源环境下缺失数据恢复框架

Durga Keshav, GVD Praneeth, Chetan Kumar Patruni, Vivek Yelleti, U Sai Ram

专题命中 领域大模型 ：large language model(title)；language model(title)

AI总结 LLMDR通过两阶段框架结合DBSCAN聚类和多LLMs实现混合数据低资源环境下的缺失数据恢复，提升数据完整性和准确性。

Actors, Frames and Arguments: A Multi-Decade Computational Analysis of Climate Discourse in Financial News using Large Language Models

行动者、框架和论点：利用大语言模型对金融新闻中气候话语的多十年计算分析

Ruiran Su, Janet B. Pierrehumbert, Markus Leippold

专题命中 领域大模型 ：large language model(title)；language model(title)

AI总结 利用大语言模型分析金融新闻中气候话语的演变，揭示了从风险与监管负担到经济机会与创新的转变，以及金融机构在其中的主导作用。

AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science

Qiuhai Zeng, Claire Jin, Xinyue Wang, Yuhan Zheng, Qunhua Li

机构 * Pennsylvania State University（宾夕法尼亚州立大学） ； Carnegie Mellon University（卡内基梅隆大学） ； International Monetary Fund（国际货币基金组织） 纠错

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

Comments Accepted to 2025 EMNLP findings

Large Language Model-Derived Priors Can Improve Bayesian Survival Analyses: A Glioblastoma Application

Richard Evans, Max Felland, Susanna Evans, Lindsey Sloan

专题命中 领域大模型 ：large language model(title)；language model(title)

Comments Presented at the 2nd Annual Southeast Wisconsin Data Science (SEAWINDS) Research Symposium, Milwaukee, WI

Who Gets Seen in the Age of AI? Adoption Patterns of Large Language Models in Scholarly Writing and Citation Outcomes

Farhan Kamrul Khan, Hazem Ibrahim, Nouar Aldahoul, Talal Rahwan, Yasir Zaki

专题命中 领域大模型 ：large language model(title)；language model(title)

Comments 11 pages, 5 figures

Cloud-Device Collaborative Agents for Sequential Recommendation

Jing Long, Sirui Huang, Huan Huo, Tong Chen, Hongzhi Yin, Guandong Xu

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

Students' Perceptions to a Large Language Model's Generated Feedback and Scores of Argumentation Essays

Winter Allen, Anand Shanker, N. Sanjay Rebello

专题命中 领域大模型 ：large language model(title)；language model(title)

Comments 7 pages, 4 figures, Physics Education Research Conference 2025

CheMatAgent: Enhancing LLMs for Chemistry and Materials Science through Tree-Search Based Tool Learning

Mengsong Wu, YaFei Wang, Yidong Ming, Yuqi An, Yuwei Wan, Wenliang Chen, Binbin Lin, Yuqiang Li, Tong Xie, Dongzhan Zhou

机构 * Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； Soochow University（苏州大学） ； Zhejiang University（浙江大学） ； City University of Hong Kong（香港城市大学） 纠错

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

Comments 15 pages, 6 figures

AstroMLab 3: Achieving GPT-4o Level Performance in Astronomy with a Specialized 8B-Parameter Large Language Model

Tijmen de Haan, Yuan-Sen Ting, Tirthankar Ghosal, Tuan Dung Nguyen, Alberto Accomazzi, Azton Wells, Nesar Ramachandra, Rui Pan, Zechang Sun

专题命中 领域大模型 ：large language model(title)；language model(title)

Journal ref Sci Rep 15, 13751 (2025)

Academic Literature Recommendation in Large-scale Citation Networks Enhanced by Large Language Models

Kun Liu, Yan Zhang, Rui Pan, Tianchen Gao, Hansheng Wang

专题命中 领域大模型 ：large language model(title)；language model(title)

Explainable Biomedical Claim Verification with Large Language Models

Siting Liang, Daniel Sonntag

专题命中 领域大模型 ：large language model(title)；language model(title)

Leveraging Large Language Models for Cybersecurity: Enhancing SMS Spam Detection with Robust and Context-Aware Text Classification

Mohsen Ahmadi, Matin Khajavi, Abbas Varmaghani, Ali Ala, Kasra Danesh, Danial Javaheri

专题命中 领域大模型 ：large language model(title)；language model(title)

Who Gets Recommended? Investigating Gender, Race, and Country Disparities in Paper Recommendations from Large Language Models

Yifan Tian, Yixin Liu, Yi Bu, Jiqun Liu

专题命中 领域大模型 ：large language model(title)；language model(title)

SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation

Abhishek Divekar, Greg Durrett

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

Comments Published as a main conference paper at EMNLP 2024. Code available at https://github.com/amazon-science/synthesizrr

Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning

Md Mushfiqur Rahman, Mohammad Sabik Irbaz, Kai North, Michelle S. Williams, Marcos Zampieri, Kevin Lybarger

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

Comments Published in Journal of Biomedical Informatics, Volume 158, October 2024, 104727

CACTUS: Chemistry Agent Connecting Tool-Usage to Science

Andrew D. McNaughton, Gautham Ramalaxmi, Agustin Kruel, Carter R. Knutson, Rohith A. Varikoti, Neeraj Kumar

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

As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making

Shomik Jain, D Calacci, Ashia Wilson

专题命中 领域大模型 ：LLM(title)；language model(title)

Comments To appear in the proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES 2024)

Diagnosis Assistant for Liver Cancer Utilizing a Large Language Model with Three Types of Knowledge

Xuzhou Wu, Guangxin Li, Xing Wang, Zeyu Xu, Yingni Wang, Jianming Xian, Xueyu Wang, Gong Li, Kehong Yuan

专题命中 领域大模型 ：large language model(title)；language model(title)

Supporting Business Document Workflows via Collection-Centric Information Foraging with Large Language Models

Raymond Fok, Nedim Lipka, Tong Sun, Alexa Siu

专题命中 领域大模型 ：large language model(title)；language model(title)

Comments 20 pages, 10 figures, 4 tables. Published at CHI 2024

Large Language Models as Data Augmenters for Cold-Start Item Recommendation

Jianling Wang, Haokai Lu, James Caverlee, Ed Chi, Minmin Chen

专题命中 领域大模型 ：large language model(title)；language model(title)

Effectively Fine-tune to Improve Large Multimodal Models for Radiology Report Generation

Yuzhe Lu, Sungmin Hong, Yash Shah, Panpan Xu

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

Comments Accepted to Deep Generative Models for Health Workshop at NeurIPS 2023

Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognition

Samuel Belkadi, Lifeng Han, Yuping Wu, Goran Nenadic

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

Comments working paper - Large Language Models, Fine-tuning LLMs, Clinical NLP, Medication Mining, AI for Healthcare