Identifying Feedback Types to Augment Feedback Comment Generation
M. Stahl, H. Wachsmuth, in: Proceedings of the 16th International Natural Language Generation Conference, n.d.

On-The-Fly Computing -- Individualized IT-services in dynamic markets
C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim, On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023.

The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments
M. Alshomary, R. El Baff, T. Gurcke, H. Wachsmuth, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 8782–8797.

"Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain
H. Wachsmuth, M. Alshomary, in: Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.

On the Role of Knowledge in  Computational Argumentation
A. Lauscher, H. Wachsmuth, I. Gurevych, G. Glavas, Transactions of the Association for Computational Linguistics (2022).

Identifying the Human Values behind Arguments
J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, B. Stein, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 4459–4471.

Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning
M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.

To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation
M. Stahl, M. Spliethöver, H. Wachsmuth, in: Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science, Abu Dhabi, United Arab Emirates, n.d.

Analyzing Culture-Specific Argument Structures in Learner Essays
W.-F. Chen, M.-H. Chen, G. Mudgal, H. Wachsmuth, in: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.

Generating Contrastive Snippets for Argument Search
M. Alshomary, J. Rieskamp, H. Wachsmuth, in: Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31.

Investigating the argumentation structures of EFL learners from diverse language backgrounds
M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.

Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale
G. Skitalinskaya, J. Klaff, H. Wachsmuth, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, 2021, pp. 1718–1729.

Overview of Touché 2021: Argument Retrieval
A. Bondarenko, L. Gienapp, M. Fröbe, M. Beloucif, Y. Ajjour, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Proceedings of the 43rd Annual European Conference on Information Retrieval Research, 2021, pp. 384–395.

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

Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models
M. Spliethöver, H. Wachsmuth, in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 2021, pp. 552–559.

Generating Informative Conclusions for Argumentative Texts
S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, M. Potthast, 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.

Syntopical Graphs for Computational Argumentation Tasks
J. Barrow, R. Jain, N. Lipka, F. Dernoncourt, V. Morariu, V. Manjunatha, D. Oard, P. Resnik, 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), 2021, pp. 1583–1595.

Employing Argumentation Knowledge Graphs for Neural Argument Generation
K. Al-Khatib, L. Trautner, H. Wachsmuth, Y. Hou, B. Stein, 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.

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.

Toward Audience-aware Argument Generation
M. Alshomary, H. Wachsmuth, Patterns 2 (2021).

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.

Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.

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.

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

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

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

Overview of Touché 2020: Argument Retrieval
A. Bondarenko, M. Fröbe, M. Beloucif, L. Gienapp, Y. Ajjour, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: CEUR Workshop Proceedings, 2020, pp. 384–395.

Intrinsic Quality Assessment of Arguments
H. Wachsmuth, T. Werner, in: Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, 2020, pp. 6739–6745.

Analyzing the Persuasive Effect of Style in News Editorial Argumentation
R. El Baff, H. Wachsmuth, K. Al-Khatib, B. Stein, in: J. Tsujii, J. Hajic (Eds.), Proceedings of 58th Annual Meeting of the Association for Computational Linguistics, 2020, pp. 553–564.

Extractive Snippet Generation for Arguments
M. Alshomary, N. Düsterhus, H. Wachsmuth, in: Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020, pp. 1969–1972.

End-to-End Argumentation Knowledge Graph Construction
K. Al-Khatib, Y. Hou, H. Wachsmuth, C. Jochim, F. Bonin, B. Stein, in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 2020, pp. 7367–7374.

Touché: First Shared Task on Argument Retrieval
A. Bondarenko, M. Hagen, M. Potthast, H. Wachsmuth, M. Beloucif, C. Biemann, A. Panchenko, B. Stein, in: Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020), 2020, pp. 517–523.

Investigating Expectations for Voice-based and Conversational Argument Search on the Web
J. Kiesel, K. Lang, H. Wachsmuth, E. Hornecker, B. Stein, in: Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction &; Retrieval (CHIIR 2020), 2020, pp. 53–62.

Visual Analysis of Argumentation in Essays
D. Kiesel, P. Riehmann, H. Wachsmuth, B. Stein, B. Fröhlich, IEEE Transactions of Visualization &; Computer Graphics 27 (n.d.) 1139–1148.

Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity
W.-F. Chen, K. Al-Khatib, H. Wachsmuth, B. Stein, in: Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 2020, pp. 149–154.

Task Proposal: Abstractive Snippet Generation for Web Pages
S. Syed, W.-F. Chen, M. Hagen, B. Stein, H. Wachsmuth, M. Potthast, in: Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020), 2020, pp. 237–241.

Detecting Media Bias in News Articles using Gaussian Bias Distributions
W.-F. Chen, K. Al-Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association for Computational Linguistics: EMNLP 2020, 2020, pp. 4290–4300.

Target Inference in Argument Conclusion Generation
M. Alshomary, S. Syed, M. Potthast, H. Wachsmuth, in: Proceedings of 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), Association for Computational Linguistics, 2020, pp. 4334–4345.

CauseNet: Towards a Causality Graph Extracted from the Web
S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030.

Argument Search: Assessing Argument Relevance
M. Potthast, L. Gienapp, F. Euchner, N. Heilenkötter, N. Weidmann, H. Wachsmuth, B. Stein, M. Hagen, in: 42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019), ACM, 2019, pp. 1117–1120.

Book Review: Argumentation Mining
H. Wachsmuth, Computational Linguistics 45 (2019) 603–606.

Data Acquisition for Argument Search: The args.me Corpus
Y. Ajjour, H. Wachsmuth, J.  Kiesel, M. Potthast, M. Hagen, B. Stein, in: Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence, 2019, pp. 48–59.

Modeling Frames in Argumentation
Y. Ajjour, M. Alshomary, H. Wachsmuth, B. Stein, in: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, 2019, pp. 2915–2925.

Proceedings of the 6th Workshop on Argument Mining
B. Stein, H. Wachsmuth, eds., Proceedings of the 6th Workshop on Argument Mining, Association for Computational Linguistics, Florence, Italy, 2019.

Computational Argumentation Synthesis as a Language Modeling Task
R. El Baff, H. Wachsmuth, K. Al-Khatib, M. Stede, B. Stein, in: Proceedings of the 12th International Conference on Natural Language Generation, Association for Computational Linguistics, 2019, pp. 54–64.