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AI 大模型

语言大模型 / LLM

大语言模型、预训练、指令微调、后训练和语言模型应用。

2025-09-05 至 2025-09-05 共收录 6 信号源:cs.CL, cs.AI, cs.LG

1. 预训练与数据 6 篇

2509.04152 2025-09-05 cs.LG cs.AI 86%

TAGAL: Tabular Data Generation using Agentic LLM Methods

Benoît Ronval, Pierre Dupont, Siegfried Nijssen

机构 * UCLouvain(乌尔特里大学) ICTEAM(信息与团队研究所) KU Leuven(根特大学) DTAI(数据与人工智能研究所)

专题命中 预训练与数据 :LLM(title,abstract);large language model(abstract);language model(abstract);分类 cs.AI、cs.LG

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2508.20038 2025-09-05 cs.CL 85%

Forewarned is Forearmed: Pre-Synthesizing Jailbreak-like Instructions to Enhance LLM Safety Guardrail to Potential Attacks

Sheng Liu, Qiang Sheng, Danding Wang, Yang Li, Guang Yang, Juan Cao

机构 * Sheng Liu Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences University of Chinese Academy of Sciences(媒体合成与取证实验室,计算技术研究所,中国科学院,中国科学院大学) Qiang Sheng Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences(媒体合成与取证实验室,计算技术研究所,中国科学院) Danding Wang Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences(媒体合成与取证实验室,计算技术研究所,中国科学院) Yang Li Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences University of Chinese Academy of Sciences(媒体合成与取证实验室,计算技术研究所,中国科学院,中国科学院大学) Guang Yang Zhongguancun Laboratory(中关村实验室) Juan Cao Media Synthesis and Forensics Lab, Institute of Computing Technology, Chinese Academy of Sciences(媒体合成与取证实验室,计算技术研究所,中国科学院)

专题命中 预训练与数据 :LLM(title,abstract);large language model(abstract);language model(abstract);分类 cs.CL

Comments EMNLP 2025 findings

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2502.18452 2025-09-05 cs.CL cs.AI 82%

FRIDA to the Rescue! Analyzing Synthetic Data Effectiveness in Object-Based Common Sense Reasoning for Disaster Response

Mollie Shichman, Claire Bonial, Austin Blodgett, Taylor Hudson, Francis Ferraro, Rachel Rudinger

机构 * University of Maryland, College Park(马里兰大学学院市分校) Army Research Lab(陆军研究实验室) Oak Ridge Associated Universities(橡树岭关联大学) University of Maryland, Baltimore County(马里兰大学巴尔的摩县分校)

专题命中 预训练与数据 :LLM(abstract);large language model(abstract);language model(abstract);prompting(abstract)

Comments 8 pages, 3 figures, 5 tables

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2509.03903 2025-09-05 cs.CV 82%

A Generative Foundation Model for Chest Radiography

Yuanfeng Ji, Dan Lin, Xiyue Wang, Lu Zhang, Wenhui Zhou, Chongjian Ge, Ruihang Chu, Xiaoli Yang, Junhan Zhao, Junsong Chen, Xiangde Luo, Sen Yang, Jin Fang, Ping Luo, Ruijiang Li

机构 * Department of Radiation Oncology, Stanford University School of Medicine(斯坦福大学医学院放射肿瘤科) Department of Computer Science, School of Computing and Data Science, The University of Hong Kong(香港大学计算机科学系) Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University(康奈尔大学兽医学院人口医学与诊断科学系) Department of Radiology, The First Affiliated Hospital of Jinan University(暨南大学第一附属医院放射科) Department of Radiology, Stanford University School of Medicine(斯坦福大学医学院放射科) Department of Computer Science and Engineering, The Chinese University of Hong Kong(香港中文大学计算机科学与工程系) Department of Biomedical Informatics, Harvard Medical School(哈佛医学院生物医学信息学系)

专题命中 预训练与数据 :foundation model(title,abstract);pretraining(abstract)

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2410.22381 2025-09-05 cs.LG cs.AI stat.CO stat.ML 62%

Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss

José Manuel de Frutos, Manuel A. Vázquez, Pablo Olmos, Joaquín Míguez

机构 * Department of Signal Theory and Communications, Carlos III University of Madrid(信号理论与通信系,卡洛斯三世大学)

专题命中 预训练与数据 :pretraining(abstract);分类 cs.AI、cs.LG

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2509.04046 2025-09-05 cs.CL 57%

A RoBERTa-Based Functional Syntax Annotation Model for Chinese Texts

Han Xiaohui, Zhang Yunlong, Guo Yuxi

机构 * Faculty of Humanities and Social Sciences(人文与社会科学学院) Harbin Institute of Technology(哈尔滨工业大学) Department of Computer Science and Engineering(计算机科学与工程系) Chalmers University of Technology(楚尔特大学)

专题命中 预训练与数据 :pretraining(abstract);分类 cs.CL

Comments The paper includes 10 pages, 6 tables, and 4 figures. This project is completed with the assistance of National Center for Language Technology and Digital Economy Research (No. GJLX20250002), and is funded by Heilongjiang Language Research Committee Project Construction of an Adaptive Intelligent Chinese Learning Platform for International Students in China (No. G2025Y003)

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