Academic literature on the topic 'AI-Assisted Learning'

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Journal articles on the topic "AI-Assisted Learning"

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Miller, Adam L. "AI Assisted Learning." Journal of e-learning Research 2, no. 2 (2023): 52–65. http://dx.doi.org/10.33422/jelr.v2i2.510.

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Both Web 4.0 and EDU 4.0 are malleable terms, that while difficult to define, set the basis for contemporary learning environments. Within these boundaries, AI (Artificial Intelligence) and AIEd (Artificial Intelligence in Education) have further complicated modern pedagogy with an ever-increasing list of potential benefits and pitfalls. This paper argues that to utilize AI and AIEd to its fullest potential, it must first be understood before it is implemented, and that while the increased presence of AI in our daily lives may be inevitable, the path it follows is not predetermined. This paper
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Dr., Amartya Saha. "Understanding the Scope and Problems of Artificial Intelligence and Assisted Learning in Higher Education." Social Science Journal for Advanced Research 4, no. 5 (2024): 1–9. https://doi.org/10.5281/zenodo.13637234.

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Learning is a dynamic experience. We need to create learning experiences that assist all kinds of learners. Human beings have different patterns of learning. Assisted learning helps in decentralizing the learning experience in a more individualistic approach. Artificial Intelligence has helped in automating many tasks of administrative nature, evaluation and has even helped personalize learning, countering the problems of teacher exhaustion. Not just efficient grading use of AI through educational chatbots and applications can help in helping students get a 24/7 mentoring option which in a rea
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Tian, Jingxiao, Hanzhe Li, Yaqian Qi, Xiangxiang Wang, and Yuan Feng. "Intelligent medical detection and diagnosis assisted by deep learning." Applied and Computational Engineering 64, no. 1 (2024): 116–21. http://dx.doi.org/10.54254/2755-2721/64/20241356.

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The integration of artificial intelligence (AI) in healthcare has led to the development of intelligent auxiliary diagnosis systems, enhancing diagnostic capabilities across various medical domains. These AI-assisted systems leverage deep learning algorithms to aid healthcare professionals in disease screening, localization of focal areas, and treatment plan selection. With policies emphasizing innovation in medical AI technology, particularly in China, AI-assisted diagnosis systems have emerged as valuable tools in improving diagnostic accuracy and efficiency. These systems, categorized into
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Guan, Heyuan. "The impact of artificial intelligence on English learning among Chinese undergraduates." Advances in Engineering Innovation 14, no. 1 (2024): 12–29. https://doi.org/10.54254/2977-3903/2024.18123.

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With the introduction of artificial intelligence (AI) into education, Chinas English education in the university has also been affected. The COVID-19 pandemic accelerated the application of AI tools in education. This study investigates the practical use of AI tools in English learning among Chinese undergraduates before, during, and after the pandemic. Students perspectives were collected through questionnaires. And its data was analyzed by using frequency analysis and multiple response analysis in SPSS. Teachers perspectives were gathered through interview. The study explored their views, at
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Supadi Supadi. "Implementation of Data-Based Management in Improving the Effectiveness of AI-Assisted Learning in Senior High School." Jurnal Ilmiah Rumpun Ilmu Pendidikan 1, no. 4 (2024): 61–82. https://doi.org/10.63760/jirip.v1i4.31.

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This study aims to analyze the implementation of data-based management in improving the effectiveness of AI-assisted learning in Senior High School. The unit of analysis in this study is a school that implements a data-based management system in AI-assisted learning. The research design used is a qualitative study with a case study approach. The research data sources consist of school principals, teachers, and students involved in the implementation of AI-assisted learning. Data collection techniques include in-depth interviews, participatory observation, and analysis of school documents. The
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N, Moulieswaran, and Prasantha Kumar N S. "Investigating ESL Learners’ Perception and Problem towards Artificial Intelligence (AI) -Assisted English Language Learning and Teaching." World Journal of English Language 13, no. 5 (2023): 290. http://dx.doi.org/10.5430/wjel.v13n5p290.

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The contemporary language learning strategy, Artificial Intelligence (AI) Assisted Language Learning (AI-ALL), incorporates AI-powered applications to support learners' learning activities. Many scholars have been experimenting with AI applications concerning activities relevant to education. The major objectives of this study are 1) The ESL learners' perspectives concerning AI-assisted English language learning and teaching; 2). ESL learners’ problems concerning artificial AI-assisted English language learning and teaching. The present investigation employed a quantitative methodology utilizi
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Okata, Ngozi Gift, and Akinsanya Atchrimi Adebayo. "Exploring (AI) Artificial Intelligence's Role in Language Teaching and Learning: A Review of Key Technologies and Their Applications." Beyond Babel: A Publication of the Dept. of Languages and Literary Studies Babcock University, Ogun State, Nigeria 8, no. 2 (2025): 50–73. https://doi.org/10.5281/zenodo.14599743.

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<strong>Abstract</strong> Artificial Intelligence (AI) is revolutionizing various aspects of education and is increasingly being integrated into language teaching and learning. This article reviews the literature to examine key trends and findings related to AI technologies and their applications for second and foreign language education. It focuses on Natural Language Processing (NLP), Data-Driven Learning (DDL), Automated Writing Evaluation (AWE), Computer-assisted Dynamic Assessment (CDA), Intelligent Tutoring Systems (ITSs), Automatic Speech Recognition (ASR), and chatbots, all within the
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Grednev, Sergej, Henrik S. Steude, Stefan Bronder, Oliver Niggemann, and Anne Jung. "AI-assisted study of auxetic structures." Acta Polytechnica CTU Proceedings 42 (October 12, 2023): 32–36. http://dx.doi.org/10.14311/app.2023.42.0032.

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In this study, the viability of using machine learning models to predict stress-strain curves of auxetic structures based on geometry-describing parameters is explored. Given the computational cost and time associated with generating these curves through numerical simulations, a machine learning-based approach promises a more efficient alternative. A range of machine learning models, including Artificial Neural Networks, k-Nearest Neighbors Regression, Support Vector Regression, and XGBoost, is implemented and compared regarding the aptitude to predict stress-strain curves under quasi-static c
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Wibowo, Setyo Aji, and Intan Faizah. "Pengaruh Model Pembelajaran Berbasis Masalah berbantuan Chatbot AI terhadap Higher Order Thinking Skill." Jurnal Nyanadassana: Jurnal Penelitian Pendidikan, Sosial dan Keagamaan 2, no. 2 (2023): 73–85. http://dx.doi.org/10.59291/jnd.v2i2.36.

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This study aims to determine the effect of problem-based learning models assisted by AI chatbots on higher-order thinking skills in Class IV at SDN 1 Genteng Kec. Genteng, Kab. Banyuwangi, East Java. This type of research uses a quantitative approach with a quasi-experimental research method and a Non-equivalent Control Group Design. Non-probability sampling was used. The population and sample consisted of 33 students in class IV-A as the experimental class and 39 students in class IV-B as the control class in SDN 1 Genteng, Kec. Genteng, Kab. Banyuwangi, East Java. The data-collection instrum
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Çela, Eriona, Mathias Mbu Fonkam, and Rajasekhara Mouly Potluri. "Risks of AI-Assisted Learning on Student Critical Thinking." International Journal of Risk and Contingency Management 12, no. 1 (2024): 1–19. http://dx.doi.org/10.4018/ijrcm.350185.

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Artificial Intelligence (AI) has increasingly become a transformative force in the education sector, offering unprecedented opportunities to enhance learning experiences and outcomes. This study examines the potential adverse effects of AI-assisted learning on critical cognitive skills, particularly critical thinking and problem-solving, within the context of Albania's educational landscape. Employing a quantitative methodology, a survey of 53 students was conducted across various educational institutions in Albania to gather data on their experiences and perceptions regarding AI-assisted lear
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Dissertations / Theses on the topic "AI-Assisted Learning"

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Taherifard, Nima. "AI-assisted Anomalous Event Detection for Connected Vehicles." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42273.

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Connected vehicle networks and future autonomous driving systems call for characterization of risky driving events to improve safety applications and autonomous driving features. Precision of driving event characterization (\gls{dec}) systems in connected vehicles has become increasingly important with the responsive connectivity that is available to the modern vehicles. While risky behavior patterns entail potential safety issues on road networks, the advent of vehicular sensing and vehicular networks cannot guarantee accurate characterization of driving/movement behavior of vehicles and the
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Maccarini, Francesco. "Modeling orchestration for computer assisted analysis and human-AI co-creativity." Electronic Thesis or Diss., Université de Lille (2022-....), 2024. http://www.theses.fr/2024ULILB047.

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L'orchestration est l'art de composer pour un ensemble d'instruments, impliquant le mélange et le contraste des timbres instrumentaux pour créer un son orchestral cohérent. Elle exige à la fois une planification artistique de haut niveau des idées musicales et un contrôle précis et minutieux des détails techniques. Chaque partie doit pouvoir être jouée sur l'instrument qui lui est propre et s'accorder avec le reste de l'ensemble.Cette thèse vise à formaliser et à élargir les connaissances sur l'orchestration en la décrivant sous l'angle des mathématiques et de l'informatique, tout en proposant
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Lee, Keon Ju. "Computer evaluation of musical timbre transfer on drum tracks." Thesis, 2021. http://hdl.handle.net/1828/13221.

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Musical timbre transfer is the task of re-rendering the musical content of a given source using the rendering style of a target sound. The source keeps its musical content, e.g., pitch, microtiming, orchestration, and syncopation. I specifically focus on the task of transferring the style of percussive patterns extracted from polyphonic audio using a MelGAN-VC model [57] by training acoustic properties for each genre. Evaluating audio style transfer is challenging and typically requires user studies. An analytical methodology based on supervised and unsupervised learning including visualizatio
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Books on the topic "AI-Assisted Learning"

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World Conference on Artificial Intelligence in Education (1997 Kobe, Japan). Artificial intelligence in education, 1997: Knowledge and media in learning systems : proceedings of AI-ED 97, World Conference on Artificial Intelligence in Education, Kobe, Japan. IOS Press, 1997.

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Montebello, Matthew. AI Injected e-Learning: The Future of Online Education. Springer, 2017.

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Montebello, Matthew. AI Injected e-Learning: The Future of Online Education. Springer, 2018.

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Verma, Shivani, and Pradeep Tomar. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education. IGI Global, 2020.

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Verma, Shivani, and Pradeep Tomar. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education. IGI Global, 2020.

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Verma, Shivani, and Pradeep Tomar. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education. IGI Global, 2020.

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Verma, Shivani, and Pradeep Tomar. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education. IGI Global, 2020.

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Verma, Shivani, and Pradeep Tomar. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education. IGI Global, 2020.

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Bhushan, Megha, Sailesh Iyer, Ashok Kumar, Tanupriya Choudhury, and Arun Negi, eds. Artificial Intelligence for Smart Cities and Villages: Advanced Technologies, Development, and Challenges. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150492511220101.

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Smart cities and villages have enhanced the quality of lives of residents. Various computer-assisted technologies have been harnessed for the development of smart cities and villages in order to provide solutions for common and niche urban problems. The development of smart environments has been possible due to advances in computing power and artificial intelligence (AI) that have allowed the deployment of scalable technologies. Artificial Intelligence for Smart Cities and Villages: Advanced Technologies, Development, and Challenges summarizes the role of AI in planning and designing smart sol
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Book chapters on the topic "AI-Assisted Learning"

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Trajkovski, Goran, and Heather Hayes. "AI-Assisted Formative Assessment and Feedback." In Digital Education and Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88252-4_7.

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Trajkovski, Goran, and Heather Hayes. "The AI-Assisted Assessment Creation Framework." In Digital Education and Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88252-4_2.

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Trajkovski, Goran, and Heather Hayes. "AI-Assisted Assessment for Diverse Learners." In Digital Education and Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88252-4_6.

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Trajkovski, Goran, and Heather Hayes. "Practical Guide: Implementing AI-Assisted Assessment." In Digital Education and Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88252-4_10.

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Trajkovski, Goran, and Heather Hayes. "Implementing AI-Assisted Assessment in Educational Institutions." In Digital Education and Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88252-4_5.

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Kurni, Muralidhar, Mujeeb Shaik Mohammed, and K. G. Srinivasa. "AI-Assisted Remote Proctored Examinations." In A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32653-0_11.

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Kohnke, Lucas. "AI Safety in Computer-Assisted Language Learning." In The Palgrave Encyclopedia of Computer-Assisted Language Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-51447-0_95-1.

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Xia, Jinling, Huafeng Liu, and Wenbin Liu. "AI-Based IWrite Assisted English Writing Teaching." In The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89511-2_19.

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Liu, Chuan, Jiaqi Shen, Yue Ren, and Hao Zheng. "Pipes of AI – Machine Learning Assisted 3D Modeling Design." In Proceedings of the 2020 DigitalFUTURES. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_2.

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AbstractStyle transfer is a design technique that is based on Artificial Intelligence and Machine Learning, which is an innovative way to generate new images with the intervention of style images. The output image will carry the characteristic of style image and maintain the content of the input image. However, the design technique is employed in generating 2D images, which has a limited range in practical use. Thus, the goal of the project is to utilize style transfer as a toolset for architectural design and find out the possibility for a 3D modeling design. To implement style transfer into
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Gryshko, Svitlana, Vagan Terziyan, and Mariia Golovianko. "Resilience Training in Higher Education: AI-Assisted Collaborative Learning." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83520-9_12.

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Conference papers on the topic "AI-Assisted Learning"

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Vaidyanathan, Kalyan, Ty Danet, TriVi Tran, and Yen Luu. "AI-assisted flight plan generation and verification." In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VII, edited by Peter J. Schwartz and Myron E. Hohil. SPIE, 2025. https://doi.org/10.1117/12.3056020.

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ElMessiry, Adel, and Magdi ElMessiry. "AGENTIC APPROACH TO AI-ASSISTED EDUCATION USING AIVP." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.1941.

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Serpi, Helena, Dimitris Alexandropoulos, and Christina (Tanya) Politi. "Scalable AI-assisted optical radio environment map estimation for indoor visible-light communication systems (AI-VLCmaps)." In Applications of Machine Learning 2025, edited by Barath Narayanan, Michael E. Zelinski, Tarek M. Taha, Abdul A. Awwal, and Khan M. Iftekharuddin. SPIE, 2025. https://doi.org/10.1117/12.3065355.

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Lu, Pingping, and Xinyi Feng. "Personalized Recommendation Algorithm in AI-Assisted Learning System." In 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2024. http://dx.doi.org/10.1109/cisce62493.2024.10653402.

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Heinisch, Cornelia. "FOSTERING COMPUTATIONAL THINKING THROUGH AI-ASSISTED TEACHING OF MULTIPLE PROGRAMMING LANGUAGES." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.0468.

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Mihaljević, Branko, Aleksander Radovan, and Dora Beronić. "INTEGRATING AI-ASSISTED LEARNING OF PROGRAMMING IN SOFTWARE DEVELOPMENT COURSES." In 17th annual International Conference of Education, Research and Innovation. IATED, 2024. https://doi.org/10.21125/iceri.2024.2623.

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Aithal, Sunil Kumar, Divyashree Devanand Naik, Deekshith, Isha Poojary, and Deeptha Rai G. "MotoWatch: Deep Learning based AI Assisted Helmet Wearing Detection System." In 2025 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2025. https://doi.org/10.1109/iciccs65191.2025.10985528.

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Sajia, Abdelali, Bilal Benzimoun, Pawan Khatiwada, Guogan Zhao, Reshawna Curley, and Xiao-Feng Qian. "AI-assisted superresolution of two practical point sources." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.jw4a.9.

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We investigate super-resolution of two spatially separated practical point sources using machine learning. High fidelity of over 90% is achieved for separations that are 16 times smaller than the conventional resolution limit.
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Chen, Jingchun. "AI-Based Feedback Model in Supporting Mobile-Assisted Language Learning Environment." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10796990.

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Umirova, Svetlana, Shavkatjon Mahmadiev, Talat Zuparov, Aziz Yuldashev, Abdulla Abdullayev, and Nazira Sobirova. "AI-Assisted Tutoring Systems: Improving Engagement and Learning Outcomes in Elementary Education." In 2024 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE, 2024. https://doi.org/10.1109/icicat62666.2024.10923307.

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Reports on the topic "AI-Assisted Learning"

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Agboola, Emmanuel O. AI-Assisted Learning for Improved Student Engagement: Lessons from the Three SSSs. The Economics Network, 2025. https://doi.org/10.53593/n4293a.

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Kruger, Scott, and Eric Howell. Final Tech-X Report for EFIT‐AI: Machine Learning and Artificial Intelligence Assisted Equilibrium Reconstruction for Tokamak Experiments and Burning Plasmas. Office of Scientific and Technical Information (OSTI), 2024. https://doi.org/10.2172/2484189.

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