Research Interests
Publications
Zeige Ergebnisse 1 - 12 von 12
2025
Spliethöver, M., Knebler, T., Fumagalli, F., Muschalik, M., Hammer, B., Hüllermeier, E., & Wachsmuth, H. (2025). Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Band 1). Association for Computational Linguistics. https://aclanthology.org/2025.naacl-long.122.pdf
2024
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 (Hrsg.), Findings of the Association for Computational Linguistics ACL 2024 (S. 9294-9313). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). https://doi.org/10.18653/v1/2024.findings-acl.553
2023
Skitalinskaya, G., Spliethöver, M., & Wachsmuth, H. (2023). Claim Optimization in Computational Argumentation. In C. M. Keet, H.-Y. Lee, & S. Zarrieß (Hrsg.), Proceedings of the 16th International Natural Language Generation Conference (S. 134-152). Association for Computational Linguistics (ACL). https://doi.org/10.48550/arXiv.2212.08913, https://doi.org/10.18653/v1/2023.inlg-main.10
2022
Spliethöver, M., Keiff, M., & Wachsmuth, H. (2022). No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media. In Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022) (S. 2081-2093). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.findings-emnlp.152
Stahl, M., Spliethöver, M., & Wachsmuth, H. (2022). To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation. In Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (S. 39-51). (NLPCSS 2022 - 5th Workshop on Natural Language Processing and Computational Social Science ,NLP+CSS, Held at the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022). Association for Computational Linguistics (ACL). https://aclanthology.org/2022.nlpcss-1.6/
2021
Alshomary, M., Gurke, T., Syed, S., Heinisch, P., Spliethöver, M., Cimiano, P., Potthast, M., & Wachsmuth, H. (2021). Key Point Analysis via Contrastive Learning and Extractive Argument Summarization. In Proceedings of The 8th Workshop on Argument Mining, (S. 184-189). Association for Computational Linguistics (ACL). https://aclanthology.org/2021.argmining-1.19.pdf
Spliethöver, M., & Wachsmuth, H. (2021). Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. In Z.-H. Zhou (Hrsg.), Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 (S. 552-559). (IJCAI International Joint Conference on Artificial Intelligence). AAAI Press/International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2021/77
2020
Alexandrovsky, D., Volkmar, G., Spliethöver, M., Finke, S., Herrlich, M., Döring, T., Smeddinck, J. D., & Malaka, R. (2020). Playful User-Generated Treatment: A Novel Game Design Approach for VR Exposure Therapy. In CHI PLAY 2020 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play (S. 32-45). Association for Computing Machinery, Inc. https://doi.org/10.1145/3410404.3414222
Spliethöver, M., & Wachsmuth, H. (2020). Argument from Old Man's View: Assessing Social Bias in Argumentation. In E. Cabrio, & S. Villata (Hrsg.), Proceedings of the 7th Workshop on Argument Mining (S. 76-87). Association for Computational Linguistics (ACL). https://aclanthology.org/2020.argmining-1.9
2019
Skitalinskaya, G., Klaff, J., & Spliethöver, M. (2019). CLEF ProtestNews Lab 2019: Contextualized word embeddings for event sentence detection and event extraction. In CLEF 2019 Working Notes: Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum (CEUR Workshop Proceedings; Band 2380). https://ceur-ws.org/Vol-2380/paper_118.pdf
Spliethöver, M., Klaff, J., & Heuer, H. (2019). Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation. In B. Stein, & H. Wachsmuth (Hrsg.), Proceedings of the 6th Workshop on Argument Mining (S. 74-82). Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-4509
2018
Bonfert, M., Spliethöver, M., Arzaroli, R., Lange, M., Hanci, M., & Porzel, R. (2018). If You Ask Nicely: A Digital Assistant Rebuking Impolite Voice Commands. In Proceedings of the 20th ACM International Conference on Multimodal Interaction (S. 95-102). Association for Computing Machinery (ACM). https://doi.org/10.1145/3242969.3242995
