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9 Publications
2024 | Conference Paper | LibreCat-ID: 55916
Booshehri, M., Buschmeier, H., & Cimiano, P. (2024). A model of factors contributing to the success of dialogical explanations. Proceedings of the 26th ACM International Conference on Multimodal Interaction, 373–381. https://doi.org/10.1145/3678957.3685744
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2024 | Conference Paper | LibreCat-ID: 55917 | 
Booshehri, M., Buschmeier, H., & Cimiano, P. (2024). Towards a BFO-based ontology of understanding in explanatory interactions. Proceedings of the 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI). 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI), Santiago de Compostela, Spain.
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2024 | Conference Paper | LibreCat-ID: 55404
Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., & Wachsmuth, H. (2024). Modeling the Quality of Dialogical Explanations. 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) (pp. 11523–11536). ELRA and ICCL.
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2024 | Conference Paper | LibreCat-ID: 58722
Spliethöver, M., Menon, S. N., & Wachsmuth, H. (2024). Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), Findings of the Association for Computational Linguistics: ACL 2024 (pp. 9294–9313). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-acl.553
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2024 | Conference Paper | LibreCat-ID: 55403 |
Buschmeier, H., Cimiano, P., Kopp, S., Kornowicz, J., Lammert, O., Matarese, M., Mindlin, D., Robrecht, A. S., Vollmer, A.-L., Wagner, P., Wrede, B., & Booshehri, M. (2024). Towards a Computational Architecture for Co-Constructive Explainable Systems. Proceedings of the 2024 Workshop on Explainability Engineering, 20–25. https://doi.org/10.1145/3648505.3648509
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2023 | Conference Paper | LibreCat-ID: 58723
Alshomary, M., & Wachsmuth, H. (2023). Conclusion-based Counter-Argument Generation. In A. Vlachos & I. Augenstein (Eds.), Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (pp. 957–967). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.eacl-main.67
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2022 | Conference Paper | LibreCat-ID: 55337
Wachsmuth, H., & Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, & S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics (pp. 344–354). International Committee on Computational Linguistics.
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2022 | Conference Paper | LibreCat-ID: 32247
Alshomary, M., Rieskamp, J., & Wachsmuth, H. (2022). Generating Contrastive Snippets for Argument Search. Proceedings of the 9th International Conference on Computational Models of Argument, 21–31. http://dx.doi.org/10.3233/FAIA220138
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2022 | Conference Paper | LibreCat-ID: 30840
Alshomary, M., El Baff, R., Gurcke, T., & Wachsmuth, H. (2022). The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 8782–8797.
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