Stahl M, Wachsmuth H. Identifying Feedback Types to Augment Feedback Comment Generation. In: Proceedings of the 16th International Natural Language Generation Conference.
LibreCat: /record/34083

Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Heinz Nixdorf Institut, Universität Paderborn; 2023. doi:10.17619/UNIPB/1-1797
LibreCat: /record/45863
DOI: 10.17619/UNIPB/1-1797

Alshomary M, El Baff R, Gurcke T, Wachsmuth H. 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. ; 2022:8782-8797.
LibreCat: /record/30840

Wachsmuth H, Alshomary M. “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. ; 2022:344-354.
LibreCat: /record/33004

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

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

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

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.
LibreCat: /record/34082

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

Alshomary M, Rieskamp J, Wachsmuth H. Generating Contrastive Snippets for Argument Search. In: Proceedings of the 9th International Conference on Computational Models of Argument. ; 2022:21-31. doi: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. Investigating the argumentation structures of EFL learners from diverse language backgrounds. In: EUROCALL. ; 2022.
LibreCat: /record/31068

Skitalinskaya G, Klaff J, Wachsmuth H. 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. ; 2021:1718-1729.
LibreCat: /record/20115

Bondarenko A, Gienapp L, Fröbe M, et al. Overview of Touché 2021: Argument Retrieval. In: Proceedings of the 43rd Annual European Conference on Information Retrieval Research. ; 2021:384-395.
LibreCat: /record/3774

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

Spliethöver M, Wachsmuth H. Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. ; 2021:552-559. doi: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. Generating Informative Conclusions for Argumentative Texts. In: 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. ; 2021:3482-3493.
LibreCat: /record/22158

Barrow J, Jain R, Lipka N, et al. Syntopical Graphs for Computational Argumentation Tasks. In: 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). ; 2021:1583-1595.
LibreCat: /record/22159

Al-Khatib K, Trautner L, Wachsmuth H, Hou Y, Stein B. Employing Argumentation Knowledge Graphs for Neural Argument Generation. In: 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). ; 2021:4744-4754.
LibreCat: /record/22160

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

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