PEER: Empowering Writing with Large Language Models. - Kathrin Seßler; Tao Xiang 003; Lukas Bogenrieder; Enkelejda Kasneci (EC-TEL, 2023)

Language Models are Realistic Tabular Data Generators. - Vadim Borisov; Kathrin Seßler; Tobias Leemann; Martin Pawelczyk; Gjergji Kasneci (ICLR, 2023)

Assessing student errors in experimentation using artificial intelligence and large language models: A comparative study with human raters. - Arne Bewersdorff; Kathrin Seßler; Armin Baur; Enkelejda Kasneci; Claudia Nerdel (Comput. Educ. Artif. Intell., 2023)

Enhancing Student Motivation Through LLM-Powered Learning Environments - A Comparative Study. - Kathrin Seßler; Ozan Kepir; Enkelejda Kasneci (EC-TEL (2), 2024)

Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education. - Arne Bewersdorff; Christian Hartmann 005; Marie Hornberger; Kathrin Seßler; Maria Bannert; Enkelejda Kasneci; Gjergji Kasneci; Xiaoming Zhai; Claudia Nerdel (CoRR, 2024)

Benchmarking Large Language Models for Math Reasoning Tasks. - Kathrin Seßler; Yao Rong; Emek Gözlüklü; Enkelejda Kasneci (CoRR, 2024)

Deep Neural Networks and Tabular Data: A Survey. - Vadim Borisov; Tobias Leemann; Kathrin Seßler; Johannes Haug; Martin Pawelczyk; Gjergji Kasneci (IEEE Trans. Neural Networks Learn. Syst., 2024)

Can AI grade your essays? A comparative analysis of large language models and teacher ratings in multidimensional essay scoring. - Kathrin Seßler; Maurice Fürstenberg; Babette Bühler; Enkelejda Kasneci (LAK, 2025)

Towards Adaptive Feedback with AI: Comparing the Feedback Quality of LLMs and Teachers on Experimentation Protocols. - Kathrin Seßler; Arne Bewersdorff; Claudia Nerdel; Enkelejda Kasneci (CoRR, 2025)

Large Language Models Don't Make Sense of Word Problems. A Scoping Review from a Mathematics Education Perspective. - Anselm R. Strohmaier; Wim Van Dooren; Kathrin Seßler; Brian Greer; Lieven Verschaffel (CoRR, 2025)