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相关论文: Integrating A.I. in Higher Education: Protocol for…

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Knowledge Tracing (KT) is a research field that aims to estimate a student's knowledge state through learning interactions-a crucial component of Intelligent Tutoring Systems (ITSs). Despite significant advancements, no current KT models…

计算机与社会 · 计算机科学 2024-12-13 Yongwan Cho , Rabia Emhamed AlMamlook , Tasnim Gharaibeh

Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, information…

计算与语言 · 计算机科学 2024-02-06 Ziqi Yang , Xuhai Xu , Bingsheng Yao , Shao Zhang , Ethan Rogers , Stephen Intille , Nawar Shara , Guodong Gordon Gao , Dakuo Wang

Advances in large language models (LLMs) are profoundly reshaping the field of human-robot interaction (HRI). While prior work has highlighted the technical potential of LLMs, few studies have systematically examined their human-centered…

机器人学 · 计算机科学 2026-02-18 Yufeng Wang , Yuan Xu , Anastasia Nikolova , Yuxuan Wang , Jianyu Wang , Chongyang Wang , Xin Tong

Large language models like ChatGPT are increasingly used in classrooms, but they often provide outdated or fabricated information that can mislead students. Retrieval Augmented Generation (RAG) improves reliability of LLMs by grounding…

人工智能 · 计算机科学 2025-09-10 Amay Jain , Liu Cui , Si Chen

6G networks aim to achieve global coverage, massive connectivity, and ultra-stringent requirements. Space-Air-Ground Integrated Networks (SAGINs) and Semantic Communication (SemCom) are essential for realizing these goals, yet they…

网络与互联网体系结构 · 计算机科学 2025-02-25 Masoud Shokrnezhad , Tarik Taleb

Recent advances in large language models (LLMs) demonstrate their potential as educational tutors. However, different tutoring strategies benefit different student personalities, and mismatches can be counterproductive to student outcomes.…

计算与语言 · 计算机科学 2026-01-14 Donya Rooein , Sankalan Pal Chowdhury , Mariia Eremeeva , Yuan Qin , Debora Nozza , Mrinmaya Sachan , Dirk Hovy

Large Language Model (LLM) tools have demonstrated their potential to deliver high-quality assistance by providing instant, personalized feedback that is crucial for effective programming education. However, many of these tools operate…

人机交互 · 计算机科学 2025-04-08 Huiyong Li , Boxuan Ma

Large Action Models (LAMs) for AI Agents offer incredible potential but face challenges due to the need for high-quality training data, especially for multi-steps tasks that involve planning, executing tool calls, and responding to…

Mental health issues significantly impact individuals' daily lives, yet many do not receive the help they need even with available online resources. This study aims to provide accessible, stigma-free, personalized, and real-time mental…

人机交互 · 计算机科学 2025-09-23 Qiming Guo , Jinwen Tang , Wenbo Sun , Haoteng Tang , Yi Shang , Wenlu Wang

The rapid development of artificial intelligence technologies, particularly Large Language Models (LLMs), has revolutionized the landscape of lifelong learning. This paper introduces a conceptual framework for a self-constructed lifelong…

计算机与社会 · 计算机科学 2024-09-25 Kirill Krinkin , Tatiana Berlenko

Our ability to continuously acquire, organize, and leverage knowledge is a key feature of human intelligence that AI systems must approximate to unlock their full potential. Given the challenges in continual learning with large language…

计算与语言 · 计算机科学 2025-06-23 Bernal Jiménez Gutiérrez , Yiheng Shu , Weijian Qi , Sizhe Zhou , Yu Su

Large Language Models (LLMs) deliver powerful AI capabilities but face deployment challenges due to high resource costs and latency, whereas Small Language Models (SLMs) offer efficiency and deployability at the cost of reduced performance.…

人工智能 · 计算机科学 2025-05-13 Yi Chen , JiaHao Zhao , HaoHao Han

Large Language Models (LLMs) suffer from hallucinations and outdated knowledge due to their reliance on static training data. Retrieval-Augmented Generation (RAG) mitigates these issues by integrating external dynamic information for…

Large Language Models (LLMs) are transforming education by enabling personalization, feedback, and knowledge access, while also raising concerns about risks to students and learning systems. Yet empirical evidence on these risks remains…

计算机与社会 · 计算机科学 2025-11-04 Iris Delikoura , Yi. R Fung , Pan Hui

In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities…

计算与语言 · 计算机科学 2024-03-22 Hanieh Alipour , Nick Pendar , Kohinoor Roy

Large language models (LLMs) show promise for improving the efficiency of qualitative analysis in large, multi-site health-services research. Yet methodological guidance for LLM integration into qualitative analysis and evidence of their…

计算与语言 · 计算机科学 2026-01-22 Sasha Ronaghi , Emma-Louise Aveling , Maria Levis , Rachel Lauren Ross , Emily Alsentzer , Sara Singer

Large language models (LLMs) have proven to work well in question-answering scenarios, but real-world applications often require access to tools for live information or actuation. For this, LLMs can be extended with tools, which are often…

This research explores the integration of chatbot technology powered by GPT-3.5 and GPT-4 Turbo into higher education to enhance internationalization and leverage digital transformation. It delves into the design, implementation, and…

计算机与社会 · 计算机科学 2024-03-25 Achraf Hsain , Hamza El Housni

Large Language Models have been increasingly employed in the creation of Virtual Assistants due to their ability to generate human-like text and handle complex inquiries. While these models hold great promise, challenges such as…

The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large language models (LLMs) might have access to sources discussing insights from educational…

人工智能 · 计算机科学 2026-05-29 Julius Gabelmann , Felix Jahn , Kevin Baum , Sophie van Rossum , Emely Wuenscher , Timo P. Gros , Verena Wolf