M. Stahl and H. Wachsmuth, “Identifying Feedback Types to Augment Feedback Comment Generation,” presented at the 16th International Natural Language Generation Conference.

C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.

M. Alshomary, R. El Baff, T. Gurcke, and H. Wachsmuth, “The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 8782–8797.

H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning How to Explain,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.

A. Lauscher, H. Wachsmuth, I. Gurevych, and G. Glavas, “On the Role of Knowledge in  Computational Argumentation,” Transactions of the Association for Computational Linguistics, 2022.

J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, and B. Stein, “Identifying the Human Values behind Arguments,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 4459–4471.

M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.

M. Stahl, M. Spliethöver, and H. Wachsmuth, “To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation,” presented at the Fifth Workshop on NLP and Computational Social Science (NLP+CSS)  At EMNLP 2022, Abu Dhabi, United Arab Emirates.

W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific Argument Structures in Learner Essays,” in Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.

M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets for Argument Search,”http://dx.doi.org/10.3233/FAIA220138__in Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31, doi:http://dx.doi.org/10.3233/FAIA220138 .