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Articles Citing

Evaluating GPT- and reasoning-based large language models on Physics Olympiad problems: Surpassing human performance and implications for educational assessment

Paul Tschisgale1, Holger Maus1, Fabian Kieser2, Ben Kroehs3, Stefan Petersen1, and Peter Wulff4

Evaluating Human Intuition, Multimodal AI, and an XGBoost Model for Estimating Ambient Population Density: A Questionnaire-Based Benchmark of Accuracy, Reasoning, and Confidence

Pasit Rojradtanasiri and Junko Tamura

Urban Sci. 10 523 (2026)

Developing an LLM-Based Feedback System Grounded in Evidence-Centered Design to Support Physics Problem Solving

Holger Maus, Fabian Kieser, Stefan Petersen, Peter Wulff, and Paul Tschisgale

The Phys. Educat. 08 2650012 (2026)

From search to GenAI queries: Global trends in physics information-seeking across topics and regions

Yossi Ben-Zion, Omer Michaeli, and Noah D. Finkelstein

Phys. Rev. Phys. Educ. Res. 22 020120 (2026)

Faculty orientations shape adoption of AI in research and teaching

T. J. Atherton, I. Descamps, M. Webel, T. R. Holmes, C. L. Vizcarra, N. Sui, and J. J. Foley

Phys. Rev. Phys. Educ. Res. 22 020152 (2026)

Superstudent intelligence in thermodynamics

Rébecca Loubet, Pascal Zittlau, Marco Hoffmann, Luisa Vollmer, Sophie Fellenz, Heike Leitte, Fabian Jirasek, Johannes Lenhard, and Hans Hasse

Phys. Educ. 61 025004 (2026)

First-class AI? Assessing LLMs on undergraduate physics exams

Ben Dowsett, Martin P Rey, and Michele Pizzochero

Phys. Educ. 61 033007 (2026)

Can artificial intelligence solve school-level physics exam questions? A decade-based evaluation using Turkish university entrance exams

Güler Çörekci and Ahmet Murat Çörekci

Phys. Educ. 61 055011 (2026)

A multi-agent collaborative framework with human-in-the-loop for well log interpretation and applications

Zhangxing CHEN, Ruichen DING, Yang MENG, Yizheng LI, Junwei ZHANG, Liu CAO, Jian LI, Wenqi FAN, Yiyuan ZHANG, Liqiu WANG, Dongxiao ZHANG, and Yuntian CHEN

Petroleum Exploration and Development 53 900 (2026)

Fine-tuning small reasoning models for quantum field theory

Nathaniel S Woodward, Zhiqi Gao, Yurii Kvasiuk, Kendrick M Smith, Frederic Sala, and Moritz Münchmeyer

Mach. Learn.: Sci. Technol. 7 055029 (2026)

The 5R's of large language model‐assisted diagnosis: A practical framework for hospitalists

Peter Barish, Andrew D. Auerbach, and Sumant R. Ranji

Journal of Hospital Medicine 21 1179 (2026)

Designing a Cross-Domain Benchmark for Large Language Models in Undergraduate Physics Education: A Monte Carlo Simulation Study

Konstantinos T. Kotsis

JETM 4 (2026)

Semiotic problem framing: a new framework to guide students and teachers in conceptual understanding and teaching of physics

M Tuveri, A Steri, and V Fanti

Eur. J. Phys. 47 015712 (2026)

How physics professors use and frame generative AI tools

Vidar Skogvoll and Tor Ole Odden

Eur. J. Phys. 47 025713 (2026)

False understanding in AI-assisted physics problem solving: a theoretical framework

Nuri Balta

Eur. J. Phys. 47 043001 (2026)

No title available

F. Škopljanac-Mačina, S. Horvatić, and D. Popović

No title available

Peter Wulff

No title available

Nicholas Young, Jasmine Freeman, Sarangan Balasubramaniam, and Nandana Weliweriya

Olympiad-Level AI Performance Is Here—What Now?

Paul Tschisgale

Physics 18 147 (2025)

Evaluating GPT- and reasoning-based large language models on Physics Olympiad problems: Surpassing human performance and implications for educational assessment

Paul Tschisgale, Holger Maus, Fabian Kieser, Ben Kroehs, Stefan Petersen, and Peter Wulff

Phys. Rev. Phys. Educ. Res. 21 020115 (2025)

Multimodal large language models and physics visual tasks: comparative analysis of performance and costs

Giulia Polverini and Bor Gregorcic

Eur. J. Phys. 46 055708 (2025)

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