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121 Publications
2022 | Conference Paper | LibreCat-ID: 33004
H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning How to Explain,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.
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2017 | Conference Paper | LibreCat-ID: 3817
H. Wachsmuth, B. Stein, and Y. Ajjour, “‘Page Rank’’’ for Argument Relevance,’” in Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 1117–1127.
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2015 | Journal Article | LibreCat-ID: 14879
W.-F. Chen, M.-H. Chen, M.-L. Chen, and L.-W. Ku, “A Computer-assistance Learning System for Emotional Wording,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 5, pp. 1093–1104, 2015.
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2016 | Conference Paper | LibreCat-ID: 3747
K. Al Khatib, H. Wachsmuth, J. Kiesel, M. Hagen, and B. Stein, “A News Editorial Corpus for Mining Argumentation Strategies,” in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 3433–3443.
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2018 | Conference Paper | LibreCat-ID: 14885
M. Potthast, W.-F. Chen, M. Hagen, and B. Stein, “A Plan for Ancillary Copyright: Original Snippets.,” in Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval, 2018, pp. 3–5.
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2014 | Conference Paper | LibreCat-ID: 20142
H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, and T. Palakarska, “A Review Corpus for Argumentation Analysis,” in Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics, 2014, pp. 115–127.
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2012 | Conference Paper | LibreCat-ID: 14871
W.-F. Chen, C.-K. Kuo, Y.-R. Wang, and S.-H. Chen, “A Syllable-based Prosody Modeling for L1 and L2 English Speeches,” in Proceedings of the 8th International Symposium on Chinese Spoken Language Processing, 2012, pp. 281–285.
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2017 | Journal Article | LibreCat-ID: 3882
H. Wachsmuth and B. Stein, “A Universal Model for Discourse-Level Argumentation Analysis,” Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media, no. 3, pp. 1–24, 2017.
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2018 | Conference Paper | LibreCat-ID: 14873
W.-F. Chen, M. Hagen, B. Stein, and M. Potthast, “A User Study on Snippet Generation: Text Reuse vs. Paraphrases,” in Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018, pp. 1033–1036.
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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 Web Conference 2020, 2020, pp. 1309–1319.
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2022 | Conference Paper | LibreCat-ID: 33274
W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific Argument Structures in Learner Essays,” in Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.
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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: 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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2018 | Journal Article | LibreCat-ID: 14887
M.-H. Chen, W.-F. Chen, and L.-W. Ku, “Application of Sentiment Analysis to Language Learning,” IEEE Access, vol. 6, pp. 24433–24442, 2018.
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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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2022 | Conference Paper | LibreCat-ID: 34051
M. Alshomary and M. Stahl, “Argument Novelty and Validity Assessment via Multitask and Transfer Learning,” in Proceedings of the 9th Workshop on Argument Mining, 2022, pp. 111–114.
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2019 | Conference Paper | LibreCat-ID: 11709
M. Potthast et al., “Argument Search: Assessing Argument Relevance,” in 42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019), 2019, pp. 1117–1120.
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2021 | Conference Paper | LibreCat-ID: 22229
M. Alshomary, S. Syed, M. Potthast, and H. Wachsmuth, “Argument Undermining: Counter-Argument Generation by Attacking Weak Premises,” 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.
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2017 | Conference Paper | LibreCat-ID: 3883
H. Wachsmuth et al., “Argumentation Quality Assessment: Theory vs. Practice,” in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2017, pp. 250–255.
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2018 | Conference Paper | LibreCat-ID: 4236
H. Wachsmuth, M. Stede, R. El Baff, K. Al Khatib, M. Skeppstedt, and B. Stein, “Argumentation Synthesis following Rhetorical Strategies,” in Proceedings of the 27th International Conference on Computational Linguistics, 2018, pp. 3753–3765.
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2021 | Conference Paper | LibreCat-ID: 25295
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.
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2013 | Conference Paper | LibreCat-ID: 3876
H. Wachsmuth, M. Rose, and G. Engels, “Automatic Pipeline Construction for Real-Time Annotation,” in 14th International Conference on Intelligent Text Processing and Computational Linguistics, 2013, pp. 38–49.
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2011 | Conference Paper | LibreCat-ID: 3811
H. Wachsmuth and K. Bujna, “Back to the Roots of Genres: Text Classification by Language Function,” in Proceedings of 5th International Joint Conference on Natural Language Processing, 2011, pp. 632–640.
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2022 | Conference Paper | LibreCat-ID: 34067
M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.
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2018 | Conference Paper | LibreCat-ID: 3806
I. Habernal, H. Wachsmuth, I. Gurevych, and B. Stein, “Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018, pp. 386–396.
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2021 | Conference Paper | LibreCat-ID: 21178
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.
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2021 | Conference Paper | LibreCat-ID: 22156 |
M. Spliethöver and H. Wachsmuth, “Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models,” in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, Online, 2021, pp. 552–559, doi: 10.24963/ijcai.2021/77.
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2019 | Book Review | LibreCat-ID: 11713
H. Wachsmuth, “Book Review: Argumentation Mining,” Computational Linguistics, vol. 45, no. 3. ACL, pp. 603–606, 2019.
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2017 | Conference Paper | LibreCat-ID: 3819
H. Wachsmuth et al., “Building an Argument Search Engine for the Web,” in Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 49–59.
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2020 | Conference Paper | LibreCat-ID: 20141 |
S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, and M. Potthast, “CauseNet: Towards a Causality Graph Extracted from the Web,” in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030, doi: 10.1145/3340531.3412763.
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2018 | Conference Paper | LibreCat-ID: 11712
R. El Baff, H. Wachsmuth, K. Al Khatib, and B. Stein, “Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus,” in Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018, pp. 454–464.
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2016 | Conference Abstract | LibreCat-ID: 14883
L.-W. Ku and W.-F. Chen, “Chinese Textual Sentiment Analysis: Datasets, Resources and Tools,” in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.
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2019 | Report | LibreCat-ID: 16847 |
G. Skitalinskaya, J. Klaff, and M. Spliethöver, CLEF ProtestNews Lab 2019: Contextualized Word Embeddings for Event Sentence Detection and Event Extraction, vol. 2380. Lugano, Switzerland, 2019.
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2017 | Conference Paper | LibreCat-ID: 3881
H. Wachsmuth et al., “Computational Argumentation Quality Assessment in Natural Language,” in Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 176–187.
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2019 | Conference Paper | LibreCat-ID: 13144
R. El Baff, H. Wachsmuth, K. Al-Khatib, M. Stede, and B. Stein, “Computational Argumentation Synthesis as a Language Modeling Task,” in Proceedings of the 12th International Conference on Natural Language Generation, Tokyo, Japan, 2019, pp. 54–64.
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2021 | Mastersthesis | LibreCat-ID: 45787
A. Mishra, Computational Text Professionalization using Neural Sequence-to-Sequence Models. 2021.
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2011 | Conference Paper | LibreCat-ID: 3875
H. Wachsmuth, B. Stein, and G. Engels, “Constructing Efficient Information Extraction Pipelines,” in 20th ACM International Conference on Information and Knowledge Management, 2011, pp. 2237–2240.
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2021 | Conference Paper | LibreCat-ID: 23709
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.
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2016 | Conference Paper | LibreCat-ID: 3801
K. Al-Khatib, H. Wachsmuth, M. Hagen, J. Köhler, and B. Stein, “Cross-Domain Mining of Argumentative Text through Distant Supervision,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016, pp. 1395–1404.
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2019 | Conference Paper | LibreCat-ID: 11714
Y. Ajjour, H. Wachsmuth, J. Kiesel, M. Potthast, M. Hagen, and B. Stein, “Data Acquisition for Argument Search: The args.me Corpus,” in Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence, 2019, pp. 48–59.
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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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2023 | Book Chapter | LibreCat-ID: 45882 |
F. S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, and H. Wachsmuth, “Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84.
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2022 | Bachelorsthesis | LibreCat-ID: 45790
J. Palushi, Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks. 2022.
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2010 | Conference Paper | LibreCat-ID: 3810
H. Wachsmuth, P. Prettenhofer, and B. Stein, “Efficient Statement Identification for Automatic Market Forecasting,” in Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), 2010, pp. 1128–1136.
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2015 | Conference Paper | LibreCat-ID: 14875
W.-F. Chen, M. Chen, and L.-W. Ku, “Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording,” in Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, 2015, pp. 144–153.
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2021 | Conference Paper | LibreCat-ID: 22160
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.
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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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2021 | Journal Article | LibreCat-ID: 24456 |
K. J. Rohlfing et al., “Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems,” IEEE Transactions on Cognitive and Developmental Systems, vol. 13, no. 3, pp. 717–728, 2021, doi: 10.1109/tcds.2020.3044366.
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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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2022 | Conference Paper | LibreCat-ID: 32247
M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets for Argument Search,” in Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31, doi: http://dx.doi.org/10.3233/FAIA220138.
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