Research Interests
I am a PhD candidate and research assistant at the NLP group at the Artificial Intelligence Institute in Hannover. I studied a bachelor of computer science at Damascus University from 2007 to 2012 and finished my master's at Bauhaus University in the faculty of Computer Science and Digital Media. In my Ph.D., I work on computationally modeling argument generation and how synthesizing arguments in natural language texts. Besides studying computational argumentation, I also focus on studying explanation dialogues and how to model their quality.
[Translate to English:] Publications
Showing results 1 - 20 out of 22
Alshomary M, Lange F, Booshehri M, Sengupta M, Cimiano P, Wachsmuth H. Modeling the Quality of Dialogical Explanations. In Calzolari N, Kan MY, Hoste V, Lenci A, Sakti S, Xue N, editors, 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings. European Language Resources Association (ELRA). 2024. p. 11523-11536. (2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings). doi: 10.48550/arXiv.2403.00662
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Chen WF, Alshomary M, Stahl M, Al Khatib K, Stein B, Wachsmuth H. Reference-guided Style-Consistent Content Transfer. In Calzolari N, Kan MY, Hoste V, Lenci A, Sakti S, Xue N, editors, 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings. European Language Resources Association (ELRA). 2024. p. 13754-13768
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Alshomary M, Wachsmuth H. Conclusion-based Counter-Argument Generation. In EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL). 2023. p. 957-967 Epub 2023 Jan 24. doi: 10.48550/arXiv.2301.09911
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Kiesel J, Alshomary M, Mirzakhmedova N, Heinrich M, Handke N, Wachsmuth H et al. SemEval-2023 Task 4: ValueEval: Identification of Human Values Behind Arguments. In Ojha AK, Doğruöz AS, Da San Martino G, Madabushi HT, Kumar R, Sartori E, editors, Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023). Association for Computational Linguistics (ACL). 2023. p. 2287-2303 doi: 10.18653/V1/2023.SEMEVAL-1.313
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Alshomary M, Stahl M. Argument Novelty and Validity Assessment via Multitask and Transfer Learning. In Proceedings of the 9th Workshop on Argument Mining. 2022. p. 111-114
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Alshomary M, Rieskamp J, Wachsmuth H. Generating Contrastive Snippets for Argument Search. In Toni F, Polberg S, Booth R, Caminada M, Kido H, editors, Computational Models of Argument: Proceedings of COMMA 2022. Amsterdam: IOS Press. 2022. p. 21-31. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/FAIA220138
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Alshomary M, El Baff R, Gurcke T, Wachsmuth H. The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. In Muresan S, Nakov P, Villavicencio A, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics Volume 1: Long Papers. Association for Computational Linguistics (ACL). 2022. p. 8782 - 8797. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.48550/arXiv.2203.14563, 10.18653/v1/2022.acl-long.601
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Kiesel J, Alshomary M, Handke N, Cai X, Wachsmuth H, Stein B. Identifying the Human Values behind Arguments. In Muresan S, Nakov P, Villavicencio A, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics Volume 1: Long Papers. Association for Computational Linguistics (ACL). 2022. p. 4459 - 4471. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2022.acl-long.306
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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. Association for Computational Linguistics (ACL). 2022. p. 137-142
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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. Gyeongju: International Committee on Computational Linguistics. 2022. p. 344 - 354 doi: 10.48550/arXiv.2209.02508
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Wachsmuth H, Alshomary M. “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In 2022 Proceedings - International Conference on Computational Linguistics, COLING. 1 ed. Vol. 29. 2022. p. 344-354. (Proceedings - International Conference on Computational Linguistics, COLING (Online)).
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Alshomary M, Chen WF, Gurcke T, Wachsmuth H. Belief-based Generation of Argumentative Claims. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics (ACL). 2021. p. 224-233 doi: 10.48550/arXiv.2101.09765, 10.18653/v1/2021.eacl-main.17
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Alshomary M, Syed S, Dhar A, Potthast M, Wachsmuth H. Counter-Argument Generation by Attacking Weak Premises: Counter-Argument Generation by Attacking Weak Premises. In Zong C, Xia F, Li W, Navigli R, editors, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics (ACL). 2021. p. 1816-1827 doi: 10.18653/v1/2021.findings-acl.159
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Alshomary M, Gurke T, Syed S, Heinisch P, Spliethöver M, Cimiano P et al. Key Point Analysis via Contrastive Learning and Extractive Argument Summarization. In Proceedings of The 8th Workshop on Argument Mining,. Association for Computational Linguistics (ACL). 2021. p. 184-189
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Alshomary M, Wachsmuth H. Toward audience-aware argument generation. Patterns. 2021 Jun;2(6):100253. doi: 10.1016/j.patter.2021.100253
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Gurcke T, Alshomary M, Wachsmuth H. Assessing the Sufficiency of Arguments through Conclusion Generation. In 8th Workshop on Argument Mining, ArgMining 2021 - Proceedings. Punta Cana: Association for Computational Linguistics (ACL). 2021. p. 67-77 doi: 10.48550/arXiv.2110.13495
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Syed S, Al-Khatib K, Alshomary M, Wachsmuth H, Potthast M. Generating Informative Conclusions for Argumentative Texts. In Zong C, Xia F, Li W, Navigli R, editors, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics (ACL). 2021. p. 3482-3493 doi: 10.48550/arXiv.2106.01064, 10.18653/v1/2021.findings-acl.306
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Alshomary M, Düsterhus N, Wachsmuth H. Extractive Snippet Generation for Arguments. In SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: Association for Computing Machinery, Inc. 2020. p. 1969-1972 doi: 10.1145/3397271.3401186
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Alshomary M, Syed S, Potthast M, Wachsmuth H. Target Inference in Argument Conclusion Generation. In Jurafsky D, Chai J, Schluter N, Tetreault J, editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. 2020. p. 4334-4345. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2020.acl-main.399
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Ajjour Y, Alshomary M, Wachsmuth H, Stein B. Modeling Frames in Argumentation. In Inui K, Jiang J, Ng V, Wan X, editors, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics. 2019. p. 2922-2932 doi: 10.18653/v1/D19-1290
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