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.

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. Alshomary and M. Stahl, “Argument Novelty and Validity Assessment via Multitask and Transfer Learning,” in Proceedings of the 9th Workshop on Argument Mining, 2022, pp. 111–114.

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 .

S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, and M. Potthast, “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, pp. 3482–3493.

M. Alshomary and H. Wachsmuth, “Toward Audience-aware Argument Generation,” Patterns, vol. 2, no. 6, 2021.

M. Alshomary et al., “Key Point Analysis via Contrastive Learning and Extractive Argument Summarization,” in Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 184–189.

T. Gurcke, M. Alshomary, and H. Wachsmuth, “Assessing the Sufficiency of Arguments through Conclusion Generation,” in Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 67–77.