InstituteStaff
Milad Alshomary

Milad Alshomary

Milad Alshomary, M. Sc.
Address
Appelstraße 9a
30167 Hannover
Building
Room
Milad Alshomary, M. Sc.
Address
Appelstraße 9a
30167 Hannover
Building
Room

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

Alshomary M, Stahl M. Argument Novelty and Validity Assessment via Multitask and Transfer Learning. 2022. Paper presented at 9th Workshop on Argument Mining, Gyeongju, Korea, Republic of.

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

doi.org/10.48550/arXiv.2203.14563

,

doi.org/10.18653/v1/2022.acl-long.601

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

doi.org/10.18653/v1/2022.acl-long.306

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

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.org/10.48550/arXiv.2209.02508

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.org/10.48550/arXiv.2101.09765

,

doi.org/10.18653/v1/2021.eacl-main.17

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.org/10.18653/v1/2021.findings-acl.159

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

Alshomary M, Wachsmuth H. Toward audience-aware argument generation. Patterns. 2021 Jun;2(6). 100253.

doi.org/10.1016/j.patter.2021.100253

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.org/10.48550/arXiv.2110.13495

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.org/10.48550/arXiv.2106.01064

,

doi.org/10.18653/v1/2021.findings-acl.306

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.org/10.1145/3397271.3401186

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

doi.org/10.18653/v1/2020.acl-main.399

Ajjour Y, Alshomary M, Wachsmuth H, Stein B. Modeling Frames in Argumentation. In 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.org/10.18653/v1/D19-1290

Alshomary M, Wachsmuth H. Siamese Neural Network for Same Side Stance Classification. CEUR Workshop Proceedings. 2019;2921:12-16.

Alshomary M, Völske M, Licht T, Wachsmuth H, Stein B, Hagen M et al. Wikipedia Text Reuse: Within and Without. In Stein B, Fuhr N, Azzopardi L, Mayr P, Hiemstra D, Hauff C, editors, Advances in Information Retrieval: 41st European Conference on IR Research, ECIR 2019, Proceedings. Springer Verlag. 2019. p. 747-754. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

doi.org/10.1007/978-3-030-15712-8_49