Milad Alshomary

Mitglied - Ehemaliger

Mitglied - Ehemaliger
Doktorand INF
Social Media in soziotechnischen Systemen
Mitglied - Ehemaliger
Research Assistant
Büro­anschrift:
Zukunftsmeile 2
33102 Paderborn
Raum:
ZM2.A.03.03

Publikationen

Aktuelle Publikationen

Analyzing the Use of Metaphors in News Editorials for Political Framing

M. Sengupta, R. El Baff, M. Alshomary, H. Wachsmuth, in: K. Duh, H. Gomez, S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Association for Computational Linguistics, Mexico City, Mexico, 2024, pp. 3621–3631.


Modeling the Quality of Dialogical Explanations

M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, H. Wachsmuth, in: N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, Torino, Italia, 2024, pp. 11523–11536.


Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms

M. Sengupta, M. Alshomary, I. Scharlau, H. Wachsmuth, in: H. Bouamor, J. Pino, K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023, Association for Computational Linguistics, Singapore, 2023, pp. 4636–4659.


The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments

M. Alshomary, R. El Baff, T. Gurcke, H. Wachsmuth, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 8782–8797.


"Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain

H. Wachsmuth, M. Alshomary, in: Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.


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Weitere Informationen

General

Hi! I am a PhD student and research assistant in the department of Computational Social Science in Paderborn University

Research Interests

  • Argument Mining and Generation
  • Deep Learning for NLP