A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Md. Mostafizer Rahman, Yutaka Watanobe
Explores ChatGPT's opportunities and threats in education and research, with coding experiments and surveys on programming learning.
Mohammad Awad AlAfnan, Samira Dishari, Marina Jovic, et al.
Empirical study of ChatGPT in communication, business writing, and composition courses, identifying opportunities, challenges, and recommendations for instructors.
Yagmur Yigit, Mohamed Amine Ferrag, Mohamed Chahine Ghanem, et al.
A review of AI-driven approaches for critical infrastructure protection, covering LLM cybersecurity benchmarks, trust and privacy issues, and agentic AI for proactive defense.
Zheng Lin, Guanqiao Qu, Qiyuan Chen, et al.
This article explores deploying large language models at the 6G edge through end-edge cooperation, discussing architecture, training, inference, and open challenges.
Rosario Michel‐Villarreal, Eliseo Luis Vilalta-perdomo, David Ernesto Salinas-Navarro, et al.
Adopts a thing ethnography approach to elicit ChatGPT's perspective on the challenges and opportunities of generative AI for higher education, emphasizing the need for policies and empirical research.
Bo Li, Yuanhan Zhang, Liangyu Chen, et al.
Otter is a multi-modal model instruction-tuned with both textual and visual in-context examples, supported by the MIMIC-IT dataset of over 3 million instruction-response pairs.
Travers H. Ching, Daniel Himmelstein, Brett K. Beaulieu‐Jones, et al.
A literature review assessing deep learning applications in biology and medicine, finding promising but modest advances and identifying key obstacles.
Mohammadreza Farrokhnia, Seyyed Kazem Banihashem, Omid Noroozi, et al.
A SWOT analysis of ChatGPT in education, outlining strengths, weaknesses, opportunities, and threats, with implications for practice and research.
Yogesh Kumar Dwivedi, Laurie Hughes, Elvira Ismagilova, et al.
A multidisciplinary expert review of AI's emerging challenges, opportunities, and research agenda across business, government, public sector, and science and technology.
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.
A position paper analyzing opportunities and challenges of using large language models in education, with recommendations for responsible and ethical integration.
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This paper examines how large language models are transforming scientific research and discusses the opportunities and challenges they present for the scientific community.
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This paper reviews synthetic data as a solution to supply chain machine learning challenges, covering methods, applications, and research opportunities.