This research explores the nuanced differences in texts produced by AI and those written by humans, aiming to elucidate how language is expressed differently by AI and humans. Through comprehensive statistical data analysis, the study investigates various linguistic traits, patterns of creativity, and potential biases inherent in human-written and AI- generated texts. The significance of this research lies in its contribution to understanding AI's creative capabilities and its impact on literature, communication, and societal frameworks. By examining a meticulously curated dataset comprising 500K essays spanning diverse topics and genres, generated by LLMs, or written by humans, the study uncovers the deeper layers of linguistic expression and provides insights into the cognitive processes underlying both AI and human-driven textual compositions. The analysis revealed that human-authored essays tend to have a higher total word count on average than AI-generated essays but have a shorter average word length compared to AI- generated essays, and while both groups exhibit high levels of fluency, the vocabulary diversity of Human authored content is higher than AI generated content. However, AI- generated essays show a slightly higher level of novelty, suggesting the potential for generating more original content through AI systems. The paper addresses challenges in assessing the language generation capabilities of AI models and emphasizes the importance of datasets that reflect the complexities of human-AI collaborative writing. Through systematic preprocessing and rigorous statistical analysis, this study offers valuable insights into the evolving landscape of AI-generated content and informs future developments in natural language processing (NLP).
Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language Models
College of Computer and Information Sciences, King Saud University（计算机与信息科学学院，沙特阿拉伯国王沙德大学）
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
LMU Munich & Munich Center for Machine Learning（慕尼黑大学及慕尼黑机器学习中心）；University of Cologne（科隆大学）；University of Augsburg（奥格斯堡大学）；Bosch Center for Artificial Intelligence（博世人工智能中心）；Columbia University（哥伦比亚大学）；University of Maryland, College Park（马里兰大学学院市分校）
NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs
Allen Institute for AI（艾伦人工智能研究所）；Association of American Medical Colleges, Center for Health Justice（美国医学院协会健康正义中心）；University of Washington（华盛顿大学）；University of California, Berkeley（加州大学伯克利分校）；University of California, San Francisco（加州大学旧金山分校）
Bhaasha, Bhasa, Zaban: A Survey for Low-Resourced Languages in South Asia -- Current Stage and Challenges
Dept of Computer Science & Engineering, West Bengal University of Technology（计算机科学与工程系，西孟加拉理工大学）；Department of Computer Science, University of Memphis（计算机科学系，孟菲斯大学）
Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models
Department of Sistemas Informáticos, Universidad Politécnica de Madrid, Spain（西班牙马德里理工大学信息系统系）；KNODIS Research Group, Universidad Politécnica de Madrid, Spain（西班牙马德里理工大学KNODIS研究组）；CIBERSAM ISCIII, Spain（西班牙ISCIII CIBERSAM）；Department of Legal Medicine, Psychiatry and Pathology. Complutense University of Madrid, Spain（西班牙马德里康普顿斯大学法医学、精神病学与病理学系）；Hospital Universitario de Móstoles, Universidad Rey Juan Carlos, Spain（西班牙雷阿尔皇家卡洛斯大学莫斯特oles大学医院）；Department of Psychiatry, University Hospital Jimenez Díaz Fundation, Madrid, Spain（西班牙圣地亚哥· jiménez Díaz基金会精神病科部）；Department of Psychiatry, University Hospital Rey Juan Carlos, Móstoles, Spain（西班牙雷阿尔皇家卡洛斯大学莫斯特oles医院精神病科部）；Department of Psychiatry, General Hospital of Villalba, Madrid, Spain（西班牙维拉尔巴医院精神病科部）；Department of Psychiatry, University Hospital Infanta Elena, Madrid, Spain（西班牙伊菲格尼亚医院精神病科部）；Department of Psychology, Universidad Catolica del Maule, Talca, Chile（智利马尔学院心理学系）；Department of Psychiatry, Madrid Autonomous University, Madrid, Spain（西班牙马德里自治大学精神病科部）
Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing
University of Amsterdam（阿姆斯特丹大学）；University of Groningen（格罗宁根大学）；University of Edinburgh（爱丁堡大学）；IT University of Copenhagen（哥本哈根信息技术大学）；Pioneer Centre for Artificial Intelligence（先锋人工智能中心）
Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection Framework
School of Information, Renmin University of China（中国人民大学信息学院）；Institute for Advanced Algorithms Research, Shanghai（上海高级算法研究院）；School of Information Technology and Management, University of International Business and Economics（对外经济贸易大学信息技术与管理学院）；Shanghai University of Finance and Economics（上海财经大学）
Evaluating Health Misinformation in Low-Resource Languages: Integrating Small Language Models with a Culturally-Sensitive Responsible NLP Framework (Bangla as a Case Study)
Western Sydney University（西悉尼大学）；Microsoft（微软公司）；Excelsia College（埃克塞尔西亚学院）；Faulconbridge Health Centre（福尔康布里奇健康中心）
Counter Turing Test CT^2: AI-Generated Text Detection is Not as Easy as You May Think -- Introducing AI Detectability Index
AI Institute, University of South Carolina（南卡罗来纳大学人工智能研究所）；IUT（伊斯兰科技大学（孟加拉国））；NIT Silchar（锡尔查尔国家理工学院）；IIIT Delhi（德里印度信息技术学院）；BITS Mesra（梅斯拉贝拉理工学院）；Stanford University（斯坦福大学）；Amazon AI（亚马逊人工智能）
本文提出Counter Turing Test (CT^2)基准评估AI生成文本检测（AGTD）技术的脆弱性，并引入AI Detectability Index (ADI)对15个LLM的可检测性进行量化排名，发现较大LLM更难被检测。
The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey
Technology Innovation Institute（技术创新研究所）；Islamic University of Technology（伊斯兰理工大学）；Stanford University（斯坦福大学）；Amazon GenAI（亚马逊生成式人工智能部门）；AI Institute, University of South Carolina（南卡罗来纳大学人工智能研究所）
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
Nanyang Technological University（南洋理工大学）；DAMO Academy, Alibaba Group（阿里达摩院）；Hupan Lab（虎斑实验室）；National University of Singapore（新加坡国立大学）；Shanda AI Research Institute（沙达AI研究院）
Fine-Grained and Multi-Dimensional Metrics for Document-Level Machine Translation
Digital Twin Institute, Eastern Institute of Technology, Ningbo, China（数字孪生研究所，东部技术研究所，宁波，中国）；Saarland University（萨尔兰州大学）；Department of Computing, The Hong Kong Polytechnic University（计算系，香港理工大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
Span-level Detection of AI-generated Scientific Text via Contrastive Learning and Structural Calibration
Beijing Renhe Information Technology Co., Ltd.（北京润和信息技术有限公司）；Key Laboratory of Digital Publishing and Total Process Management of Scientific and Technical Journals（科技期刊数字出版与全流程管理重点实验室）
FAID: Fine-Grained AI-Generated Text Detection Using Multi-Task Auxiliary and Multi-Level Contrastive Learning
BKAI Research Center, Hanoi University of Science and Technology（河内科学技术大学BKAI研究中心）；MBZUAI；INSAIT, Sofia University "St. Kliment Ohridski"（索菲亚大学"圣克莱门特·奥赫里德斯"INSAIT）
