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相关论文: AGGA: A Dataset of Academic Guidelines for Generat…

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This paper introduces IGGA, a dataset of 160 industry guidelines and policy statements for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in industry and workplace settings, collected from official company websites, and…

计算机与社会 · 计算机科学 2025-03-19 Junfeng Jiao , Saleh Afroogh , Kevin Chen , David Atkinson , Amit Dhurandhar

The integration of Generative Artificial Intelligence (GAI) and Large Language Models (LLMs) in academia has spurred a global discourse on their potential pedagogical benefits and ethical considerations. Positive reactions highlight some…

计算机与社会 · 计算机科学 2025-03-19 Junfeng Jiao , Saleh Afroogh , Kevin Chen , David Atkinson , Amit Dhurandhar

Generative AI models have shown impressive performance on many Natural Language Processing tasks such as language understanding, reasoning, and language generation. An important question being asked by the AI community today is about the…

The rapid proliferation of generative artificial intelligence (AI) tools - especially large language models (LLMs) such as ChatGPT - has ushered in a transformative era in higher education. Universities in developed regions are increasingly…

人机交互 · 计算机科学 2025-06-30 Russell Beale

The rise of Generative AI (GAI) and Large Language Models (LLMs) has transformed industrial landscapes, offering unprecedented opportunities for efficiency and innovation while raising critical ethical, regulatory, and operational…

计算机与社会 · 计算机科学 2026-03-11 Junfeng Jiao , Saleh Afroogh , Kevin Chen , David Atkinson , Amit Dhurandhar

The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear…

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a…

Generative artificial intelligence (GenAI) holds great promise as a tool to support personalized learning. Teachers need tools to efficiently and effectively enhance content readability of educational texts so that they are matched to…

Natural language generation (NLG) is the key technology to achieve generative artificial intelligence (AI). With the breakthroughs in large language models (LLMs), NLG has been widely used in various medical applications, demonstrating the…

计算与语言 · 计算机科学 2025-05-08 Mengxian Lyu , Xiaohan Li , Ziyi Chen , Jinqian Pan , Cheng Peng , Sankalp Talankar , Yonghui Wu

Generative artificial intelligence attracts significant attention, especially with the introduction of large language models. Its capabilities are being exploited to solve various software engineering tasks. Thanks to their ability to…

软件工程 · 计算机科学 2026-02-06 Lukas Radosky , Ivan Polasek

The release of ChatGPT in November 2022 prompted a massive uptake of generative artificial intelligence (GenAI) across higher education institutions (HEIs). HEIs scrambled to respond to its use, especially by students, looking first to…

计算机与社会 · 计算机科学 2024-02-06 Nora McDonald , Aditya Johri , Areej Ali , Aayushi Hingle

Generative AI (GAI) technologies are quickly reshaping the educational landscape. As adoption accelerates, understanding how students and educators perceive these tools is essential. This study presents one of the most comprehensive…

社会与信息网络 · 计算机科学 2026-01-07 Paulina DeVito , Akhil Vallala , Sean Mcmahon , Yaroslav Hinda , Benjamin Thaw , Hanqi Zhuang , Hari Kalva

Recent regulatory initiatives like the European AI Act and relevant voices in the Machine Learning (ML) community stress the need to describe datasets along several key dimensions for trustworthy AI, such as the provenance processes and…

数字图书馆 · 计算机科学 2024-05-27 Joan Giner-Miguelez , Abel Gómez , Jordi Cabot

Graphical Abstracts (GAs) play a crucial role in visually conveying the key findings of scientific papers. Although recent research increasingly incorporates visual materials such as Figure 1 as de facto GAs, their potential to enhance…

计算机视觉与模式识别 · 计算机科学 2026-04-07 Takuro Kawada , Shunsuke Kitada , Sota Nemoto , Hitoshi Iyatomi

Automatic survey generation has emerged as a key task in scientific document processing. While large language models (LLMs) have shown promise in generating survey texts, the lack of standardized evaluation datasets critically hampers…

计算与语言 · 计算机科学 2025-08-26 Tong Bao , Mir Tafseer Nayeem , Davood Rafiei , Chengzhi Zhang

Examining limitations is a crucial step in the scholarly research reviewing process, revealing aspects where a study might lack decisiveness or require enhancement. This aids readers in considering broader implications for further research.…

计算与语言 · 计算机科学 2024-06-17 Abdur Rahman Bin Md Faizullah , Ashok Urlana , Rahul Mishra

Providing timely, consistent, and high-quality feedback in large-scale higher education courses remains a persistent challenge, often constrained by instructor workload and resource limitations. This study presents an LLM-powered, agentic…

计算机与社会 · 计算机科学 2026-01-13 Reza Vatankhah Barenji , Nazila Salimi , Sina Khoshgoftar

Academic paper review typically requires substantial time, expertise, and human resources. Large Language Models (LLMs) present a promising method for automating the review process due to their extensive training data, broad knowledge base,…

计算机与社会 · 计算机科学 2025-06-24 Chuanlei Li , Xu Hu , Minghui Xu , Kun Li , Yue Zhang , Xiuzhen Cheng

Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, general-purpose applications. In this technical report, we…

Background: Over the past few decades, the process and methodology of automated question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the…

人工智能 · 计算机科学 2024-12-06 Dominic Lohr , Marc Berges , Abhishek Chugh , Michael Kohlhase , Dennis Müller
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