Research Interests
Publications
Showing results 1 - 5 out of 5
2024
Ziegenbein, T., Skitalinska, G., Bayat Makou, A., & Wachsmuth, H. (2024). LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback. In L.-W. Ku, A. F. T. Martins, & V. Srikumar (Eds.), Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Vol. 1, pp. 4455-4476). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.48550/arXiv.2406.03363, https://doi.org/10.18653/v1/2024.acl-long.244
2023
Skitalinskaya, G., Spliethöver, M., & Wachsmuth, H. (2023). Claim Optimization in Computational Argumentation. In C. M. Keet, H.-Y. Lee, & S. Zarrieß (Eds.), Proceedings of the 16th International Natural Language Generation Conference (pp. 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
Skitalinskaya, G., & Wachsmuth, H. (2023). To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 15799–15816). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.acl-long.880
2021
Skitalinskaya, G., Klaff, J., & Wachsmuth, H. (2021). Learning from revisions: Quality assessment of claims in argumentation at scale. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (pp. 1718-1729). Association for Computational Linguistics (ACL). https://doi.org/10.48550/arXiv.2101.10250, https://doi.org/10.18653/v1/2021.eacl-main.147
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; Vol. 2380). https://ceur-ws.org/Vol-2380/paper_118.pdf
