Nouri Z, Gadiraju U, Engels G, Wachsmuth H. What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing. In HT 2021 - Proceedings of the 32nd ACM Conference on Hypertext and Social Media. Association for Computing Machinery, Inc. 2021. p. 165-175 doi: 10.1145/3465336.3475109

Skitalinskaya G, Klaff J, Wachsmuth H. 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. Association for Computational Linguistics (ACL). 2021. p. 1718-1729 doi: 10.48550/arXiv.2101.10250, 10.18653/v1/2021.eacl-main.147

Spliethöver M, Wachsmuth H. Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. In Zhou Z-H, editor, Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021. AAAI Press/International Joint Conferences on Artificial Intelligence. 2021. p. 552-559. (IJCAI International Joint Conference on Artificial Intelligence). doi: 10.24963/ijcai.2021/77

Syed S, Al-Khatib K, Alshomary M, Wachsmuth H, Potthast M. Generating Informative Conclusions for Argumentative Texts. In Zong C, Xia F, Li W, Navigli R, editors, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics (ACL). 2021. p. 3482-3493 doi: 10.48550/arXiv.2106.01064, 10.18653/v1/2021.findings-acl.306

Alshomary M, Düsterhus N, Wachsmuth H. Extractive Snippet Generation for Arguments. In SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: Association for Computing Machinery, Inc. 2020. p. 1969-1972 doi: 10.1145/3397271.3401186

Alshomary M, Syed S, Potthast M, Wachsmuth H. Target Inference in Argument Conclusion Generation. In Jurafsky D, Chai J, Schluter N, Tetreault J, editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. 2020. p. 4334-4345. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2020.acl-main.399

Bondarenko A, Fröbe M, Beloucif M, Gienapp L, Ajjour Y, Panchenko A et al. Overview of Touché 2020: Argument Retrieval: Extended Abstract. In Arampatzis A, Kanoulas E, Tsikrika T, Vrochidis S, Joho H, Lioma C, Eickhoff C, Névéol A, Névéol A, Cappellato L, Ferro N, editors, Experimental IR Meets Multilinguality, Multimodality, and Interaction: 11th International Conference of the CLEF Association, CLEF 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 384-395. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-58219-7_26

Bondarenko A, Hagen M, Potthast M, Wachsmuth H, Beloucif M, Biemann C et al. Touché: First Shared Task on Argument Retrieval. In Jose JM, Yilmaz E, Magalhães J, Martins F, Castells P, Ferro N, Silva MJ, editors, Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020. Springer. 2020. p. 517-523. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-45442-5_67

Chen W-F, Al-Khatib K, Wachsmuth H, Stein B. Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity. In Bamman D, Hovy D, Jurgens D, O'Connor B, Volkova S, editors, Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science. Association for Computational Linguistics (ACL). 2020. p. 149-154 doi: 10.18653/v1/2020.nlpcss-1.16

Chen WF, Al-Khatib K, Stein B, Wachsmuth H. Detecting Media Bias in News Articles using Gaussian Bias Distributions. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics (ACL). 2020. p. 4290-4300 doi: 10.48550/arXiv.2010.10649, 10.18653/v1/2020.findings-emnlp.383

da San Martino G, Barrón-Cedeño A, Wachsmuth H, Petrov R, Nakov P. SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. In Herbelot A, Zhu X, Palmer A, Schneider N, May J, Shutova E, editors, Proceedings of the 14th International Workshop on Semantic Evaluation. Barcelona : International Committee for Computational Linguistics. 2020. p. 1377-1414 doi: 10.48550/arXiv.2009.02696, 10.18653/v1/2020.semeval-1.186

Dorsch J, Wachsmuth H. Semi-Supervised Cleansing of Web Argument Corpora. In Cabrio E, Villata S, editors, Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics (ACL). 2020. p. 19-29 doi: 10.48550/arXiv.2011.01798

El Baff R, Wachsmuth H, Al-Khatib K, Stein B. Analyzing the Persuasive Effect of Style in News Editorial Argumentation. In Jurafsky D, Chai J, Schluter N, Tetreault J, editors, Proceedings of 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics (ACL). 2020. p. 3154-3160. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2020.acl-main.287

El Baff R, Al-Khatib K, Stein B, Wachsmuth H. Persuasiveness of News Editorials depending on Ideology and Personality. In Nissim M, Patti V, Plank B, Durmus E, editors, Proceedings of the Third Workshop on Computational Modeling of PEople’s Opinions, PersonaLity, and Emotions in Social media. Association for Computational Linguistics (ACL). 2020. p. 29-40

Heindorf S, Scholten Y, Wachsmuth H, Ngonga Ngomo AC, Potthast M. CauseNet: Towards a Causality Graph Extracted from the Web. In CIKM' 2020: Proceedings of the 29th ACM International Conference on Information and Knowledge Management. New York: Association for Computing Machinery (ACM). 2020. p. 3023-3030 doi: 10.1145/3340531.3412763

Kiesel J, Lang K, Wachsmuth H, Hornecker E, Stein B. Investigating Expectations for Voice-based and Conversational Argument Search on the Web. In CHIIR 2020: Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. New York: Association for Computing Machinery, Inc. 2020. p. 53-62 doi: 10.1145/3343413.3377978