Stahl, M., &; Wachsmuth, H. (n.d.). Identifying Feedback Types to Augment Feedback Comment Generation. Proceedings of the 16th International Natural Language Generation Conference. 16th International Natural Language Generation Conference.
LibreCat: /record/34083

Haake, C.-J., Meyer auf der Heide, F., Platzner, M., Wachsmuth, H., &; Wehrheim, H. (2023). On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412). Heinz Nixdorf Institut, Universität Paderborn.https://doi.org/10.17619/UNIPB/1-1797 
LibreCat: /record/45863
DOI: 10.17619/UNIPB/1-1797

Alshomary, M., El Baff, R., Gurcke, T., &; Wachsmuth, H. (2022). The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 8782–8797.
LibreCat: /record/30840

Wachsmuth, H., &; Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning How to Explain. Proceedings of the 29th International Conference on Computational Linguistics, 344–354.
LibreCat: /record/33004

Lauscher, A., Wachsmuth, H., Gurevych, I., &; Glavas, G. (2022). On the Role of Knowledge in  Computational Argumentation. Transactions of the Association for Computational Linguistics.
LibreCat: /record/34049

Kiesel, J., Alshomary, M., Handke, N., Cai, X., Wachsmuth, H., &; Stein, B. (2022). Identifying the Human Values behind Arguments. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 4459–4471.
LibreCat: /record/22157

Sengupta, M., Alshomary, M., &; Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 2022 Workshop on Figurative Language Processing.
LibreCat: /record/34067

Stahl, M., Spliethöver, M., &; Wachsmuth, H. (n.d.). To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation. Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science. Fifth Workshop on NLP and Computational Social Science (NLP+CSS)  At EMNLP 2022, Abu Dhabi, United Arab Emirates.
LibreCat: /record/34082

Chen, W.-F., Chen, M.-H., Mudgal, G., &; Wachsmuth, H. (2022). Analyzing Culture-Specific Argument Structures in Learner Essays. Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 51–61.
LibreCat: /record/33274

Alshomary, M., Rieskamp, J., &; Wachsmuth, H. (2022). Generating Contrastive Snippets for Argument Search. Proceedings of the 9th International Conference on Computational Models of Argument, 21–31.http://dx.doi.org/10.3233/FAIA220138 
LibreCat: /record/32247
DOI: http://dx.doi.org/10.3233/FAIA220138

Chen, M.-H., Mudgal, G., Chen, W.-F., &; Wachsmuth, H. (2022). Investigating the argumentation structures of EFL learners from diverse language backgrounds. EUROCALL.
LibreCat: /record/31068

Skitalinskaya, G., Klaff, J., &; Wachsmuth, H. (2021). Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (pp. 1718–1729).
LibreCat: /record/20115

Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko, A.,  Hagen, M. (2021). Overview of Touché 2021: Argument Retrieval. In Proceedings of the 43rd annual European Conference on Information Retrieval Research (pp. 384–395).
LibreCat: /record/3774

Nouri, Z., Gadiraju, U., Engels, G., &; Wachsmuth, H. (2021). What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing. Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 165–175.
LibreCat: /record/23708

Spliethöver, M., &; Wachsmuth, H. (2021). Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 552–559.https://doi.org/10.24963/ijcai.2021/77 
LibreCat: /record/22156
DOI: 10.24963/ijcai.2021/77

Syed, S., Al-Khatib, K., Alshomary, M., Wachsmuth, H., &; Potthast, M. (2021). Generating Informative Conclusions for Argumentative Texts. Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021): Findings, 3482–3493.
LibreCat: /record/22158

Barrow, J., Jain, R., Lipka, N., Dernoncourt, F., Morariu, V., Manjunatha, V., Oard, D., Resnik, P., &; Wachsmuth, H. (2021). Syntopical Graphs for Computational Argumentation Tasks. Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 1583–1595.
LibreCat: /record/22159

Al-Khatib, K., Trautner, L., Wachsmuth, H., Hou, Y., &; Stein, B. (2021). Employing Argumentation Knowledge Graphs for Neural Argument Generation. Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 4744–4754.
LibreCat: /record/22160

Kiesel, J., Spina, D., Wachsmuth, H., &; Stein, B. (2021). The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases. Proceedings of the 2021 Conversational User Interfaces Conference, 1–5.
LibreCat: /record/22448

Alshomary, M., &; Wachsmuth, H. (2021). Toward Audience-aware Argument Generation. Patterns, 2(6).
LibreCat: /record/22449