Research Interests
Publications
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1
Kilsbach S, Rezat S, Michel N, Karabey R, Stahl M, Wachsmuth H. Mehrebenenannotation argumentativer Lerner∗innentexte für die automatische Textauswertung. Zeitschrift fur Angewandte Linguistik. 2025 Mär 13;82(1):102–129. doi: 10.1515/zfal-2025-2003
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Rezat S, Kilsbach S, Karabey R, Michel N, Stahl M, Wachsmuth H. Didaktische Modellierung automatisierten adaptiven Feedbacks zu argumentativen Lerner* innentexten. Leseräume: Zeitschrift für Literalität in Schule und Forschung. 2025;12(11).
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Stahl M, Ziegenbein T, Park J, Wachsmuth H. ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation. in Che W, Nabende J, Shutova E, Pilehvar MT, Hrsg., Findings of the Association for Computational Linguistics: ACL 2025. 2025. S. 11103–11127. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2025.findings-acl.579
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Chen WF, Alshomary M, Stahl M, Al Khatib K, Stein B, Wachsmuth H. Reference-guided Style-Consistent Content Transfer. in Calzolari N, Kan MY, Hoste V, Lenci A, Sakti S, Xue N, Hrsg., 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings. European Language Resources Association (ELRA). 2024. S. 13754-13768
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Stahl M, Michel N, Kilsbach S, Schmidtke J, Rezat S, Wachsmuth H. A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality. in Duh K, Gomez H, Bethard S, Hrsg., Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024. S. 2661–2674 doi: 10.18653/v1/2024.naacl-long.145, 10.48550/arXiv.2404.02529
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Stahl M, Biermann L, Nehring A, Wachsmuth H. Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation. in Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024). 2024. S. 283–298
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Stahl M, Wachsmuth H. Identifying Feedback Types to Augment Feedback Comment Generation. in Mille S, Hrsg., INLG 2023 - 16th International Natural Language Generation Conference: Generation Challenges, Proceedings of the Generation Challenges. 2023. S. 31-36 doi: 10.18653/v1/2023.inlg-genchal.5
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Stahl M, Düsterhus N, Chen MH, Wachsmuth H. Mind the Gap: Automated Corpus Creation for Enthymeme Detection and Reconstruction in Learner Arguments. in Findings of the Association for Computational Linguistics: EMNLP 2023. 2023. S. 4703-4717 doi: 10.48550/arXiv.2310.18098, 10.18653/v1/2023.findings-emnlp.312
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Alshomary M, Stahl M. Argument Novelty and Validity Assessment via Multitask and Transfer Learning. in Proceedings of the 9th Workshop on Argument Mining. 14 Aufl. Band 29. 2022. S. 111-114. (Proceedings - International Conference on Computational Linguistics, COLING).
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Stahl M, Spliethöver M, Wachsmuth H. To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation. in Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science. Abu Dhabi, United Arab Emirates: Association for Computational Linguistics (ACL). 2022. S. 39-51. (NLPCSS 2022 - 5th Workshop on Natural Language Processing and Computational Social Science ,NLP+CSS, Held at the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022).
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