Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness

Spliethöver, M., Menon, S. N. & Wachsmuth, H., Aug. 2024, Findings of the Association for Computational Linguistics ACL 2024. Ku, L.-W., Martins, A. & Srikumar, V. (Hrsg.). S. 9294-9313 20 S. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

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Analyzing the Use of Metaphors in News Editorials for Political Framing

Sengupta, M., El Baff, R., Alshomary, M. & Wachsmuth, H., Juni 2024, Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Duh, K., Gomez, H. & Bethard, S. (Hrsg.). Mexico City, Mexico, S. 3621–3631 11 S. (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Band 1).

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A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality

Stahl, M., Michel, N., Kilsbach, S., Schmidtke, J., Rezat, S. & Wachsmuth, H., Juni 2024, Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Duh, K., Gomez, H. & Bethard, S. (Hrsg.). S. 2661–2674 14 S. (Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024; Band 1).

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Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation

Stahl, M., Biermann, L., Nehring, A. & Wachsmuth, H., Juni 2024, Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024). S. 283–298

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Reference-guided Style-Consistent Content Transfer

Chen, W. F., Alshomary, M., Stahl, M., Al Khatib, K., Stein, B. & Wachsmuth, H., 2024, 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings. Calzolari, N., Kan, M.-Y., Hoste, V., Lenci, A., Sakti, S. & Xue, N. (Hrsg.). S. 13754-13768 15 S.

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Claim Optimization in Computational Argumentation

Skitalinskaya, G., Spliethöver, M. & Wachsmuth, H., Sept. 2023, Proceedings of the 16th International Natural Language Generation Conference. Keet, C. M., Lee, H.-Y. & Zarrieß, S. (Hrsg.). S. 134-152

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Identifying Feedback Types to Augment Feedback Comment Generation

Stahl, M. & Wachsmuth, H., Sept. 2023, Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges. S. 31-36

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Perspectives on Large Language Models for Relevance Judgment

Faggioli, G., Clarke, C. L. A., Demartini, G., Hagen, M., Hauff, C., Kando, N., Kanoulas, E., Potthast, M., Stein, B., Wachsmuth, H. & Dietz, L., 9 Aug. 2023, ICTIR '23: Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval. S. 39-50 12 S.

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Modeling Appropriate Language in Argumentation

Ziegenbein, T., Syed, S., Lange, F., Potthast, M. & Wachsmuth, H., Juli 2023, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. S. 4344-4363 20 S. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Band 1).

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SemEval-2023 Task 4: ValueEval: Identification of Human Values Behind Arguments

Kiesel, J., Alshomary, M., Mirzakhmedova, N., Heinrich, M., Handke, N., Wachsmuth, H. & Stein, B., Juli 2023, Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023). Ojha, A. K., Doğruöz, A. S., Da San Martino, G., Madabushi, H. T., Kumar, R. & Sartori, E. (Hrsg.). S. 2287-2303 17 S.

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To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support

Skitalinskaya, G. & Wachsmuth, H., Juli 2023, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). S. 15799–15816 17 S. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Band 1).

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Dialogue-Based Requirement Compensation and Style-Adjusted Data-To-Text Generation

Bäumer, F., Chen, W. F., Geierhos, M., Kersting, J. & Wachsmuth, H., 2023, On-The-Fly Computing : Individualized IT-Services in dynamic markets. S. 65-84

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Frame-oriented Summarization of Argumentative Discussions

Syed, S., Ziegenbein, T., Heinisch, P., Wachsmuth, H. & Potthast, M., 2023, Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue. S. 114-129

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Mind the Gap: Automated Corpus Creation for Enthymeme Detection and Reconstruction in Learner Arguments

Stahl, M., Düsterhus, N., Chen, M. & Wachsmuth, H., 2023, Findings of the Association for Computational Linguistics: EMNLP 2023. S. 4703-4717

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Topic Ontologies for Arguments

Ajjour, Y., Kiesel, J., Stein, B. & Potthast, M., 2023, Findings of the Association for Computational Linguistics: EACL 2023. Kroatien, S. 1411–1427

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Topic Ontologies for Arguments

Ajjour, Y., Stein, B., Kiesel, J. & Potthast, M., 2023, EACL 2023 : 17th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2023. S. 1381-1397 17 S.

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No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media

Spliethöver, M., Keiff, M. & Wachsmuth, H., Dez. 2022, Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). S. 2081-2093 13 S.

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To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation

Stahl, M., Spliethöver, M. & Wachsmuth, H., Nov. 2022, Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science. Abu Dhabi, United Arab Emirates, S. 39-51 13 S. (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).

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