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

Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
M. Alshomary, T. Gurcke, S. Syed, P. Heinisch, M. Spliethöver, P. Cimiano, M. Potthast, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 184–189.

iClarify - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing
Z. Nouri, N. Prakash, U. Gadiraju, H. Wachsmuth, in: Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021, 2021.

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

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

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

Argument Undermining: Counter-Argument Generation by Attacking Weak Premises
M. Alshomary, S. Syed, M. Potthast, H. Wachsmuth, 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), Association for Computational Linguistics, 2021, pp. 1816–1827.

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

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

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