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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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2021 | Conference Paper | LibreCat-ID: 22158 |
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.
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2017 | Conference Paper | LibreCat-ID: 14884
W.-F. Chen, Y.-P. Chen, and L.-W. Ku, “How to Get Endorsements? Predicting Facebook Likes Using Post Content and User Engagement,” in International Conference on HCI in Business, Government, and Organizations, 2017, pp. 190–202.
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2021 | Conference Paper | LibreCat-ID: 25294
Z. Nouri, N. Prakash, U. Gadiraju, and H. Wachsmuth, “iClarify - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing,” 2021.
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2023 | Conference Paper | LibreCat-ID: 34083
M. Stahl and H. Wachsmuth, “Identifying Feedback Types to Augment Feedback Comment Generation,” presented at the 16th International Natural Language Generation Conference.
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2022 | Conference Paper | LibreCat-ID: 22157
J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, and B. Stein, “Identifying the Human Values behind Arguments,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 4459–4471.
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2018 | Conference Paper | LibreCat-ID: 21173
M. Bonfert, M. Spliethöver, R. Arzaroli, M. Lange, M. Hanci, and R. Porzel, “If You Ask Nicely: A Digital Assistant Rebuking Impolite Voice Commands,” in Proceedings of the 20th ACM International Conference on Multimodal Interaction, 2018.
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2013 | Conference Paper | LibreCat-ID: 3814
H. Wachsmuth, B. Stein, and G. Engels, “Information Extraction as a Filtering Task,” in Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management, 2013, pp. 2049–2058.
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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: 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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2022 | Conference Abstract | LibreCat-ID: 31068
M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation structures of EFL learners from diverse language backgrounds,” 2022.
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2019 | Conference Paper | LibreCat-ID: 21177 |
M. Spliethöver, J. Klaff, and H. Heuer, “Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation,” in Proceedings of the 6th Workshop on Argument Mining, Florence, Italy, 2019, pp. 74–82.
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2014 | Journal Article | LibreCat-ID: 3905
C. Abu Quba Rana, S. Hassas, F. Usama, M. Alshomary, and C. Gertosio, “iSoNTRE: The Social Network Transformer into Recommendation Engine,” 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), pp. 169–175, 2014.
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2021 | Conference Paper | LibreCat-ID: 25297
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.
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2022 | Mastersthesis | LibreCat-ID: 29000
M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing. 2022.
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2013 | Conference Paper | LibreCat-ID: 3813
H. Wachsmuth, B. Stein, and G. Engels, “Learning Efficient Information Extraction on Heterogeneous Texts,” in Proceedings of the Sixth International Joint Conference on Natural Language Processing, 2013, pp. 534–542.
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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, pp. 1718–1729.
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2018 | Conference Paper | LibreCat-ID: 11710
W.-F. Chen, H. Wachsmuth, K. Al Khatib, and B. Stein, “Learning to Flip the Bias of News Headlines,” in Proceedings of the 11th International Conference on Natural Language Generation, 2018, pp. 79–88.
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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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2015 | Conference Paper | LibreCat-ID: 14877
W.-F. Chen, L.-W. Ku, and Y.-H. Lee, “Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example,” in 2015 AAAI Spring Symposium Series, 2015.
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2018 | Conference Paper | LibreCat-ID: 3804
K. Al Khatib, H. Wachsmuth, K. Lang, J. Herpel, M. Hagen, and B. Stein, “Modeling Deliberative Argumentation Strategies on Wikipedia,” in Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 2545–2555.
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2019 | Conference Paper | LibreCat-ID: 12931
Y. Ajjour, M. Alshomary, H. Wachsmuth, and B. Stein, “Modeling Frames in Argumentation,” 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.
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2014 | Conference Paper | LibreCat-ID: 3877
H. Wachsmuth, M. Trenkmann, B. Stein, and G. Engels, “Modeling Review Argumentation for Robust Sentiment Analysis,” in Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, 2014, pp. 553–564.
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2022 | Conference Paper | LibreCat-ID: 34047
M. Spliethöver, M. Keiff, and H. Wachsmuth, “No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media,” presented at the The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi, 2022.
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2022 | Journal Article | LibreCat-ID: 34049
A. Lauscher, H. Wachsmuth, I. Gurevych, and G. Glavaš, “On the Role of Knowledge in Computational Argumentation,” Transactions of the Association for Computational Linguistics, 2022.
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2023 | Book | LibreCat-ID: 45863 |
C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.
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2012 | Conference Paper | LibreCat-ID: 3812
H. Wachsmuth and B. Stein, “Optimal Scheduling of Information Extraction Algorithms,” in Proceedings of COLING 2012: Posters, 2012, pp. 1281–1290.
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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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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, pp. 384–395.
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2017 | Conference Paper | LibreCat-ID: 3803
K. Al Khatib, H. Wachsmuth, M. Hagen, and B. Stein, “Patterns of Argumentation Strategies across Topics,” in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 1362–1368.
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2014 | Conference Paper | LibreCat-ID: 3805
F. Brüseke, H. Wachsmuth, G. Engels, and S. Becker, “PBlaman: performance blame analysis based on Palladio contracts,” in Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment, 2014, no. 12, pp. 1975–2004.
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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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2015 | Dissertation | LibreCat-ID: 7568
H. Wachsmuth, Pipelines for Ad-hoc Large-scale Text Mining. 2015.
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2016 | Conference Paper | LibreCat-ID: 3880
H. Wachsmuth, “Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse,” in Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329–338.
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2020 | Conference Paper | LibreCat-ID: 21174
D. Alexandrovsky et al., “Playful User-Generated Treatment: A Novel Game Design Approach for VR Exposure Therapy,” in Proceedings of the Annual Symposium on Computer-Human Interaction in Play, 2020, pp. 32–45.
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2021 | Mastersthesis | LibreCat-ID: 45788
J. Bülling, Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump. 2021.
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2019 | Conference (Editor) | LibreCat-ID: 15235
B. Stein and H. Wachsmuth, Eds., Proceedings of the 6th Workshop on Argument Mining. Florence, Italy: Association for Computational Linguistics, 2019.
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2022 | Mastersthesis | LibreCat-ID: 45789
V. Budanurmath, Propaganda Technique Detection Using Connotation Frames. 2022.
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2018 | Journal Article | LibreCat-ID: 10331
J. Kiesel, F. Kneist, M. Alshomary, B. Stein, M. Hagen, and M. Potthast, “Reproducible Web Corpora,” Journal of Data and Information Quality, pp. 1–25, 2018.
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2014 | Conference Paper | LibreCat-ID: 14874
M.-H. Chen, W.-F. Chen, and L.-W. Ku, “RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’ Emotional Expressions,” in Proceedings of the AsiaCALL 2014, 2014.
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2018 | Conference Paper | LibreCat-ID: 3821
H. Wachsmuth, S. Syed, and B. Stein, “Retrieval of the Best Counterargument without Prior Topic Knowledge,” in Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 241–251.
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2018 | Conference Paper | LibreCat-ID: 3807
I. Habernal, H. Wachsmuth, I. Gurevych, and B. Stein, “SemEval-2018 Task 12: The Argument Reasoning Comprehension Task,” in Proceedings of The 12th International Workshop on Semantic Evaluation, 2018, pp. 763–772.
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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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2015 | Conference Paper | LibreCat-ID: 3815
H. Wachsmuth, J. Kiesel, and B. Stein, “Sentiment Flow - A General Model of Web Review Argumentation,” in Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015, pp. 601–611.
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2007 | Conference Paper | LibreCat-ID: 7970
S. Arens et al., “Smart Teams: Simulating Large Robotic Swarms in Vast Environments,” in Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment, 2007, pp. 215–222.
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2021 | Conference Paper | LibreCat-ID: 22159 |
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.
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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: 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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2015 | Conference Paper | LibreCat-ID: 14876
M.-H. Chen, W.-F. Chen, and L.-W. Ku, “Technology Enhanced Emotion Expression Learning,” 2015.
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