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83 Publications


2021 | Conference Paper | LibreCat-ID: 20115
G. Skitalinskaya, J. Klaff, and H. Wachsmuth, “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, 2021.
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2021 | Conference Paper | LibreCat-ID: 3774
A. Bondarenko et al., “Overview of Touché 2021: Argument Retrieval,” in Proceedings of the 43rd annual European Conference on Information Retrieval Research, 2021.
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2021 | Preprint | LibreCat-ID: 21178
M. Alshomary, W.-F. Chen, T. Gurcke, and H. Wachsmuth, “Belief-based Generation of Argumentative Claims,” Proceedings of the 43rd annual European Conference on Information Retrieval Research. 2021.
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2020 | Conference Paper | LibreCat-ID: 20140
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.
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2020 | Conference Paper | LibreCat-ID: 15820
K. Al-Khatib, Y. Hou, H. Wachsmuth, C. Jochim, F. Bonin, and B. Stein, “End-to-End Argumentation Knowledge Graph Construction,” in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 2020, pp. 7367–7374.
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2020 | Conference Paper | LibreCat-ID: 15825
J. Kiesel, K. Lang, H. Wachsmuth, E. Hornecker, and B. Stein, “Investigating Expectations for Voice-based and Conversational Argument Search on the Web,” in Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2020), 2020, pp. 53–62.
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2020 | Conference Paper | LibreCat-ID: 3776
W.-F. Chen, K. Al-Khatib, H. Wachsmuth, and B. Stein, “Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity,” in Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 2020, pp. 149–154.
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2020 | Conference Paper | LibreCat-ID: 20122
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.
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2020 | Conference Paper | LibreCat-ID: 20139
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.
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2020 | Conference Paper | LibreCat-ID: 15826
W.-F. Chen, S. Syed, B. Stein, M. Hagen, and M. Potthast, “Abstractive Snippet Generation,” in Proceedings of the the Web Conference 2020, 2020, pp. 1309–1319.
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2020 | Conference Paper | LibreCat-ID: 3878
R. El Baff, H. Wachsmuth, K. Al-Khatib, and B. Stein, “Analyzing the Persuasive Effect of Style in News Editorial Argumentation,” in Proceedings of 58th Annual Meeting of the Association for Computational Linguistics, 2020, pp. 553–564.
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2020 | Conference Paper | LibreCat-ID: 15821
A. Bondarenko et al., “Touché: First Shared Task on Argument Retrieval,” in Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020), 2020, pp. 517–523.
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2020 | Conference Paper | LibreCat-ID: 20116
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.
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2020 | Conference Paper | LibreCat-ID: 20166
A. Bondarenko et al., “Overview of Touché 2020: Argument Retrieval,” in CEUR Workshop Proceedings, 2020, vol. 2696, pp. 384–395.
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2020 | Conference Paper | LibreCat-ID: 16868
M. Alshomary, S. Syed, M. Potthast, and H. Wachsmuth, “Target Inference in Argument Conclusion Generation,” in Proceedings of 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), Seattle, USA, 2020, pp. 4334–4345.
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2020 | Conference Paper | LibreCat-ID: 3800
H. Wachsmuth and T. Werner, “Intrinsic Quality Assessment of Arguments,” in Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, 2020, pp. 6739–6745.
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2020 | Conference Paper | LibreCat-ID: 7283
M. Alshomary, N. Düsterhus, and H. Wachsmuth, “Extractive Snippet Generation for Arguments,” in Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Xi’an, China, 2020, pp. 1969–1972.
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2020 | Conference Paper | LibreCat-ID: 20137
S. Syed, W.-F. Chen, M. Hagen, B. Stein, H. Wachsmuth, and M. Potthast, “Task Proposal: Abstractive Snippet Generation for Web Pages,” in Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020), 2020, pp. 237–241.
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2020 | Conference Paper | LibreCat-ID: 3818
W.-F. Chen, K. Al-Khatib, B. Stein, and H. Wachsmuth, “Detecting Media Bias in News Articles using Gaussian Bias Distributions,” in Findings of the Association for Computational Linguistics: EMNLP 2020, 2020, pp. 4290–4300.
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2020 | Journal Article | LibreCat-ID: 10330
D. Kiesel, P. Riehmann, H. Wachsmuth, B. Stein, and B. Fröhlich, “Visual Analysis of Argumentation in Essays,” IEEE Transactions of Visualization & Computer Graphics, vol. 27, no. 2, pp. 1139–1148.
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