Z. Nouri, U. Gadiraju, G. Engels, and H. Wachsmuth, “What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing,” in Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 2021, pp. 165–175.

M. Spliethöver and H. Wachsmuth, “Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models,”10.24963/ijcai.2021/77__in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, Online, 2021, pp. 552–559, doi:10.24963/ijcai.2021/77 .

S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, and M. Potthast, “Generating Informative Conclusions for Argumentative Texts,” in Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021): Findings, 2021, pp. 3482–3493.

J. Barrow et al., “Syntopical Graphs for Computational Argumentation Tasks,” in Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 2021, pp. 1583–1595.

K. Al-Khatib, L. Trautner, H. Wachsmuth, Y. Hou, and B. Stein, “Employing Argumentation Knowledge Graphs for Neural Argument Generation,” in Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 2021, pp. 4744–4754.

J. Kiesel, D. Spina, H. Wachsmuth, and B. Stein, “The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases,” in Proceedings of the 2021 Conversational User Interfaces Conference, 2021, pp. 1–5.

M. Alshomary and H. Wachsmuth, “Toward Audience-aware Argument Generation,” Patterns, vol. 2, no. 6, 2021.

M. Alshomary et al., “Key Point Analysis via Contrastive Learning and Extractive Argument Summarization,” in Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 184–189.

Z. Nouri, N. Prakash, U. Gadiraju, and H. Wachsmuth, Clarify - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing,” 2021.

T. Gurcke, M. Alshomary, and H. Wachsmuth, “Assessing the Sufficiency of Arguments through Conclusion Generation,” in Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 67–77.

M. Alshomary, W.-F. Chen, T. Gurcke, and H. Wachsmuth, “Belief-based Generation of Argumentative Claims,” in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Online, 2021, pp. 224–223.

W.-F. Chen, K. Al Khatib, B. Stein, and H. Wachsmuth, “Controlled Neural Sentence-Level Reframing of News Articles,” in Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.

M. Alshomary, S. Syed, M. Potthast, and H. Wachsmuth, “Argument Undermining: Counter-Argument Generation by Attacking Weak Premises,”10.18653/v1/2021.findings-acl.159__in Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Online, 2021, pp. 1816–1827, doi:10.18653/v1/2021.findings-acl.159 .

J. Bülling, Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump. 2021.

A. Mishra, Computational Text Professionalization using Neural Sequence-to-Sequence Models. 2021.

K. J. Rohlfing et al., “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems,”10.1109/tcds.2020.3044366__IEEE Transactions on Cognitive and Developmental Systems, vol. 13, no. 3, pp. 717–728, 2021, doi:10.1109/tcds.2020.3044366 .

Z. Nouri, H. Wachsmuth, and G. Engels, “Mining Crowdsourcing Problems from Discussion Forums of Workers,” in Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, Barcelona, Spain, pp. 6264–6276.

R. El Baff, K. Al-Khatib, B. Stein, and H. Wachsmuth, “Persuasiveness of News Editorials depending on Ideology and Personality,” in Third Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES 2020), 2020, pp. 29–40.

M. Spliethöver and H. Wachsmuth, “Argument from Old Man’s View: Assessing Social Bias in Argumentation,” in Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 76–87.

J. Dorsch and H. Wachsmuth, “Semi-Supervised Cleansing of Web Argument Corpora,” in Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 19–29.