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97 Publications
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2025 | Conference Paper | LibreCat-ID: 61190
M. Sengupta et al., “Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions,” presented at the Empirical Methods in Natural Language Processing (EMNLP 2025), 2025.
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2025 | Conference Paper | LibreCat-ID: 61234 | 
L. Fichtel et al., “Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues,” presented at the Annual Meeting of the Special Interest Group on Discourse and Dialogue.
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2025 | Conference Paper | LibreCat-ID: 59856 |
M. Spliethöver et al., “Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection,” in Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2025, pp. 2421–2449.
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2024 | Conference Paper | LibreCat-ID: 55338
M. Sengupta, R. El Baff, M. Alshomary, and H. Wachsmuth, “Analyzing the Use of Metaphors in News Editorials for Political Framing,” in Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024, pp. 3621–3631.
LibreCat
2024 | Conference Paper | LibreCat-ID: 55404
M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, and H. Wachsmuth, “Modeling the Quality of Dialogical Explanations,” in Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 2024, pp. 11523–11536.
LibreCat
2024 | Conference Paper | LibreCat-ID: 58722 |
M. Spliethöver, S. N. Menon, and H. Wachsmuth, “Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness,” in Findings of the Association for Computational Linguistics: ACL 2024, 2024, pp. 9294–9313, doi: 10.18653/v1/2024.findings-acl.553.
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2023 | Conference Paper | LibreCat-ID: 34083
M. Stahl and H. Wachsmuth, “Identifying Feedback Types to Augment Feedback Comment Generation,” presented at the 16th International Natural Language Generation Conference.
LibreCat
2023 | Book | LibreCat-ID: 45863 |
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.
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2023 | Conference Paper | LibreCat-ID: 55406
M. Sengupta, M. Alshomary, I. Scharlau, and H. Wachsmuth, “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms,” in Findings of the Association for Computational Linguistics: EMNLP 2023, 2023, pp. 4636–4659, doi: 10.18653/v1/2023.findings-emnlp.308.
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2023 | Conference Paper | LibreCat-ID: 58723
M. Alshomary and H. Wachsmuth, “Conclusion-based Counter-Argument Generation,” in Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023, pp. 957–967, doi: 10.18653/v1/2023.eacl-main.67.
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2022 | Conference Paper | LibreCat-ID: 33004
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.
LibreCat
2022 | Journal Article | LibreCat-ID: 34049
A. Lauscher, H. Wachsmuth, I. Gurevych, and G. Glavaš, “On the Role of Knowledge in Computational Argumentation,” Transactions of the Association for Computational Linguistics, 2022.
LibreCat
2022 | Conference Paper | LibreCat-ID: 22157
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.
LibreCat
2022 | Conference Paper | LibreCat-ID: 34082
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.
LibreCat
2022 | Conference Paper | LibreCat-ID: 33274
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.
LibreCat
2022 | Conference Abstract | LibreCat-ID: 31068
M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation structures of EFL learners from diverse language backgrounds,” 2022.
LibreCat
2022 | Conference Paper | LibreCat-ID: 55337
H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.
LibreCat
2022 | Conference Paper | LibreCat-ID: 34067
M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.
LibreCat
2022 | Conference Paper | LibreCat-ID: 32247
M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets for Argument Search,” in Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31, doi: http://dx.doi.org/10.3233/FAIA220138.
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2022 | Conference Paper | LibreCat-ID: 30840
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.
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