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Wachsmuth, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 8782–8797."},"type":"conference","year":"2022","page":"8782 - 8797"},{"status":"public","date_created":"2022-08-18T10:00:46Z","author":[{"last_name":"Wachsmuth","id":"3900","first_name":"Henning","full_name":"Wachsmuth, Henning"},{"full_name":"Alshomary, Milad","first_name":"Milad","id":"73059","last_name":"Alshomary"}],"department":[{"_id":"600"}],"publication":"Proceedings of the 29th International Conference on Computational Linguistics","title":"\"Mama Always Had a Way of Explaining Things So I Could Understand\": A Dialogue Corpus for Learning How to Explain","user_id":"82920","citation":{"mla":"Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning How to Explain.” Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–54.","bibtex":"@inproceedings{Wachsmuth_Alshomary_2022, title={“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning How to Explain}, booktitle={Proceedings of the 29th International Conference on Computational Linguistics}, author={Wachsmuth, Henning and Alshomary, Milad}, year={2022}, pages={344–354} }","ama":"Wachsmuth H, Alshomary M. “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning How to Explain. 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Alshomary, in: Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354."},"type":"conference","year":"2022","page":"344 - 354","language":[{"iso":"eng"}],"date_updated":"2022-11-10T09:06:39Z","_id":"33004"},{"citation":{"ieee":"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.","short":"A. Lauscher, H. Wachsmuth, I. Gurevych, G. Glavaš, Transactions of the Association for Computational Linguistics (2022).","mla":"Lauscher, Anne, et al. “On the Role of Knowledge in Computational Argumentation.” Transactions of the Association for Computational Linguistics, 2022.","bibtex":"@article{Lauscher_Wachsmuth_Gurevych_Glavaš_2022, title={On the Role of Knowledge in Computational Argumentation}, journal={Transactions of the Association for Computational Linguistics}, author={Lauscher, Anne and Wachsmuth, Henning and Gurevych, Iryna and Glavaš, Goran}, year={2022} }","apa":"Lauscher, A., Wachsmuth, H., Gurevych, I., & Glavaš, G. (2022). On the Role of Knowledge in Computational Argumentation. Transactions of the Association for Computational Linguistics.","ama":"Lauscher A, Wachsmuth H, Gurevych I, Glavaš G. On the Role of Knowledge in Computational Argumentation. Transactions of the Association for Computational Linguistics. Published online 2022.","chicago":"Lauscher, Anne, Henning Wachsmuth, Iryna Gurevych, and Goran Glavaš. “On the Role of Knowledge in Computational Argumentation.” Transactions of the Association for Computational Linguistics, 2022."},"type":"journal_article","year":"2022","language":[{"iso":"eng"}],"_id":"34049","date_updated":"2022-11-10T08:39:48Z","date_created":"2022-11-10T08:39:38Z","status":"public","department":[{"_id":"600"}],"publication":"Transactions of the Association for Computational Linguistics","author":[{"last_name":"Lauscher","full_name":"Lauscher, Anne","first_name":"Anne"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"},{"first_name":"Iryna","full_name":"Gurevych, Iryna","last_name":"Gurevych"},{"last_name":"Glavaš","full_name":"Glavaš, Goran","first_name":"Goran"}],"title":"On the Role of Knowledge in Computational Argumentation","user_id":"82920"},{"date_created":"2021-05-11T23:15:42Z","status":"public","department":[{"_id":"600"}],"publication":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics","author":[{"last_name":"Kiesel","first_name":"Johannes","full_name":"Kiesel, Johannes"},{"first_name":"Milad","full_name":"Alshomary, Milad","last_name":"Alshomary","id":"73059"},{"last_name":"Handke","first_name":"Nicolas","full_name":"Handke, Nicolas"},{"full_name":"Cai, Xiaoni","first_name":"Xiaoni","last_name":"Cai"},{"last_name":"Wachsmuth","id":"3900","first_name":"Henning","full_name":"Wachsmuth, Henning"},{"last_name":"Stein","first_name":"Benno","full_name":"Stein, Benno"}],"title":"Identifying the Human Values behind Arguments","user_id":"82920","page":"4459 - 4471","citation":{"bibtex":"@inproceedings{Kiesel_Alshomary_Handke_Cai_Wachsmuth_Stein_2022, title={Identifying the Human Values behind Arguments}, booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics}, author={Kiesel, Johannes and Alshomary, Milad and Handke, Nicolas and Cai, Xiaoni and Wachsmuth, Henning and Stein, Benno}, year={2022}, pages={4459–4471} }","mla":"Kiesel, Johannes, et al. “Identifying the Human Values behind Arguments.” Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 4459–71.","chicago":"Kiesel, Johannes, Milad Alshomary, Nicolas Handke, Xiaoni Cai, Henning Wachsmuth, and Benno Stein. “Identifying the Human Values behind Arguments.” In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 4459–71, 2022.","ama":"Kiesel J, Alshomary M, Handke N, Cai X, Wachsmuth H, Stein B. Identifying the Human Values behind Arguments. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics. ; 2022:4459-4471.","apa":"Kiesel, J., Alshomary, M., Handke, N., Cai, X., Wachsmuth, H., & Stein, B. (2022). Identifying the Human Values behind Arguments. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 4459–4471.","ieee":"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.","short":"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."},"year":"2022","type":"conference","language":[{"iso":"eng"}],"_id":"22157","date_updated":"2022-11-10T09:09:27Z"},{"status":"public","date_created":"2022-11-10T08:28:53Z","publisher":"Association for Computational Linguistics","author":[{"last_name":"Spliethöver","first_name":"Maximilian","full_name":"Spliethöver, Maximilian"},{"last_name":"Keiff","first_name":"Maximilian","full_name":"Keiff, Maximilian"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","last_name":"Wachsmuth"}],"department":[{"_id":"600"}],"publication":"Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)","title":"No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media","user_id":"84035","extern":"1","external_id":{"arxiv":["2211.03634"]},"abstract":[{"text":"News articles both shape and reflect public opinion across the political\r\nspectrum. Analyzing them for social bias can thus provide valuable insights,\r\nsuch as prevailing stereotypes in society and the media, which are often\r\nadopted by NLP models trained on respective data. Recent work has relied on\r\nword embedding bias measures, such as WEAT. However, several representation\r\nissues of embeddings can harm the measures' accuracy, including low-resource\r\nsettings and token frequency differences. In this work, we study what kind of\r\nembedding algorithm serves best to accurately measure types of social bias\r\nknown to exist in US online news articles. To cover the whole spectrum of\r\npolitical bias in the US, we collect 500k articles and review psychology\r\nliterature with respect to expected social bias. We then quantify social bias\r\nusing WEAT along with embedding algorithms that account for the aforementioned\r\nissues. We compare how models trained with the algorithms on news articles\r\nrepresent the expected social bias. Our results suggest that the standard way\r\nto quantify bias does not align well with knowledge from psychology. While the\r\nproposed algorithms reduce the~gap, they still do not fully match the\r\nliterature.","lang":"eng"}],"citation":{"ieee":"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.","mla":"Spliethöver, Maximilian, et al. “No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media.” Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Association for Computational Linguistics, 2022.","bibtex":"@inproceedings{Spliethöver_Keiff_Wachsmuth_2022, title={No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media}, booktitle={Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)}, publisher={Association for Computational Linguistics}, author={Spliethöver, Maximilian and Keiff, Maximilian and Wachsmuth, Henning}, year={2022} }","short":"M. Spliethöver, M. Keiff, H. Wachsmuth, in: Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Association for Computational Linguistics, 2022.","ama":"Spliethöver M, Keiff M, Wachsmuth H. No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media. In: Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). Association for Computational Linguistics; 2022.","apa":"Spliethöver, M., Keiff, M., & Wachsmuth, H. (2022). No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media. Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi.","chicago":"Spliethöver, Maximilian, Maximilian Keiff, and Henning Wachsmuth. “No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media.” In Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). Association for Computational Linguistics, 2022."},"year":"2022","type":"conference","language":[{"iso":"eng"}],"_id":"34047","date_updated":"2022-11-11T12:49:47Z","conference":{"end_date":"2022-12-11","name":"The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)","start_date":"2022-12-07","location":"Abu Dhabi"}},{"date_created":"2022-11-14T08:49:07Z","status":"public","publication":"Proceedings of the 2022 Workshop on Figurative Language Processing","department":[{"_id":"600"}],"author":[{"last_name":"Sengupta","full_name":"Sengupta, Meghdut","first_name":"Meghdut"},{"first_name":"Milad","full_name":"Alshomary, Milad","last_name":"Alshomary","id":"73059"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","id":"3900"}],"user_id":"82920","title":"Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning","language":[{"iso":"eng"}],"type":"conference","citation":{"bibtex":"@inproceedings{Sengupta_Alshomary_Wachsmuth_2022, title={Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning}, booktitle={Proceedings of the 2022 Workshop on Figurative Language Processing}, author={Sengupta, Meghdut and Alshomary, Milad and Wachsmuth, Henning}, year={2022} }","mla":"Sengupta, Meghdut, et al. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.","apa":"Sengupta, M., Alshomary, M., & Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 2022 Workshop on Figurative Language Processing.","ama":"Sengupta M, Alshomary M, Wachsmuth H. Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. In: Proceedings of the 2022 Workshop on Figurative Language Processing. ; 2022.","chicago":"Sengupta, Meghdut, Milad Alshomary, and Henning Wachsmuth. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” In Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.","ieee":"M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.","short":"M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop on Figurative Language Processing, 2022."},"year":"2022","date_updated":"2022-11-14T08:49:15Z","_id":"34067"},{"place":"Cham","user_id":"52174","title":"Overview of Touché 2022: Argument Retrieval","author":[{"full_name":"Bondarenko, Alexander","first_name":"Alexander","last_name":"Bondarenko"},{"last_name":"Fröbe","full_name":"Fröbe, Maik","first_name":"Maik"},{"last_name":"Kiesel","first_name":"Johannes","full_name":"Kiesel, Johannes"},{"last_name":"Syed","first_name":"Shahbaz","full_name":"Syed, Shahbaz"},{"full_name":"Gurcke, Timon","first_name":"Timon","last_name":"Gurcke"},{"first_name":"Meriem","full_name":"Beloucif, Meriem","last_name":"Beloucif"},{"full_name":"Panchenko, Alexander","first_name":"Alexander","last_name":"Panchenko"},{"full_name":"Biemann, Chris","first_name":"Chris","last_name":"Biemann"},{"last_name":"Stein","full_name":"Stein, Benno","first_name":"Benno"},{"last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","first_name":"Henning"},{"first_name":"Martin","full_name":"Potthast, Martin","last_name":"Potthast"},{"full_name":"Hagen, Matthias","first_name":"Matthias","last_name":"Hagen"}],"publisher":"Springer International Publishing","department":[{"_id":"600"}],"publication":"Lecture Notes in Computer Science","status":"public","date_created":"2022-11-14T13:47:51Z","alternative_title":["Extended Abstract"],"publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783030997380","9783030997397"]},"publication_status":"published","_id":"34077","date_updated":"2022-11-14T13:48:38Z","doi":"10.1007/978-3-030-99739-7_43","citation":{"ieee":"A. Bondarenko et al., “Overview of Touché 2022: Argument Retrieval,” in Lecture Notes in Computer Science, Cham: Springer International Publishing, 2022.","short":"A. Bondarenko, M. Fröbe, J. Kiesel, S. Syed, T. Gurcke, M. Beloucif, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Lecture Notes in Computer Science, Springer International Publishing, Cham, 2022.","mla":"Bondarenko, Alexander, et al. “Overview of Touché 2022: Argument Retrieval.” Lecture Notes in Computer Science, Springer International Publishing, 2022, doi:10.1007/978-3-030-99739-7_43.","bibtex":"@inbook{Bondarenko_Fröbe_Kiesel_Syed_Gurcke_Beloucif_Panchenko_Biemann_Stein_Wachsmuth_et al._2022, place={Cham}, title={Overview of Touché 2022: Argument Retrieval}, DOI={10.1007/978-3-030-99739-7_43}, booktitle={Lecture Notes in Computer Science}, publisher={Springer International Publishing}, author={Bondarenko, Alexander and Fröbe, Maik and Kiesel, Johannes and Syed, Shahbaz and Gurcke, Timon and Beloucif, Meriem and Panchenko, Alexander and Biemann, Chris and Stein, Benno and Wachsmuth, Henning and et al.}, year={2022} }","apa":"Bondarenko, A., Fröbe, M., Kiesel, J., Syed, S., Gurcke, T., Beloucif, M., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., & Hagen, M. 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Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-030-99739-7_43."},"type":"book_chapter","year":"2022"},{"language":[{"iso":"eng"}],"page":"51 - 61","type":"conference","citation":{"mla":"Chen, Wei-Fan, et al. “Analyzing Culture-Specific Argument Structures in Learner Essays.” Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.","bibtex":"@inproceedings{Chen_Chen_Mudgal_Wachsmuth_2022, title={Analyzing Culture-Specific Argument Structures in Learner Essays}, booktitle={Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)}, author={Chen, Wei-Fan and Chen, Mei-Hua and Mudgal, Garima and Wachsmuth, Henning}, year={2022}, pages={51–61} }","apa":"Chen, W.-F., Chen, M.-H., Mudgal, G., & Wachsmuth, H. (2022). Analyzing Culture-Specific Argument Structures in Learner Essays. Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 51–61.","ama":"Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument Structures in Learner Essays. In: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022). ; 2022:51-61.","chicago":"Chen, Wei-Fan, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. “Analyzing Culture-Specific Argument Structures in Learner Essays.” In Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 51–61, 2022.","ieee":"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.","short":"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."},"year":"2022","date_updated":"2022-11-18T09:56:17Z","_id":"33274","publication":"Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)","department":[{"_id":"600"}],"author":[{"first_name":"Wei-Fan","full_name":"Chen, Wei-Fan","last_name":"Chen","id":"82920"},{"last_name":"Chen","first_name":"Mei-Hua","full_name":"Chen, Mei-Hua"},{"full_name":"Mudgal, Garima","first_name":"Garima","last_name":"Mudgal"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"}],"project":[{"_id":"9","name":"SFB 901 - B1: SFB 901 - Subproject B1"},{"_id":"1","name":"SFB 901: SFB 901"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"}],"date_created":"2022-09-06T13:51:23Z","status":"public","user_id":"477","title":"Analyzing Culture-Specific Argument Structures in Learner Essays"},{"status":"public","date_created":"2022-06-28T09:03:30Z","author":[{"full_name":"Alshomary, Milad","first_name":"Milad","id":"73059","last_name":"Alshomary"},{"id":"77643","last_name":"Rieskamp","full_name":"Rieskamp, Jonas","first_name":"Jonas"},{"last_name":"Wachsmuth","id":"3900","first_name":"Henning","full_name":"Wachsmuth, Henning"}],"publication":"Proceedings of the 9th International Conference on Computational Models of Argument","department":[{"_id":"600"}],"user_id":"77643","title":"Generating Contrastive Snippets for Argument Search","language":[{"iso":"eng"}],"type":"conference","year":"2022","citation":{"mla":"Alshomary, Milad, et al. “Generating Contrastive Snippets for Argument Search.” Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31, doi:http://dx.doi.org/10.3233/FAIA220138.","bibtex":"@inproceedings{Alshomary_Rieskamp_Wachsmuth_2022, title={Generating Contrastive Snippets for Argument Search}, DOI={http://dx.doi.org/10.3233/FAIA220138}, booktitle={Proceedings of the 9th International Conference on Computational Models of Argument}, author={Alshomary, Milad and Rieskamp, Jonas and Wachsmuth, Henning}, year={2022}, pages={21–31} }","chicago":"Alshomary, Milad, Jonas Rieskamp, and Henning Wachsmuth. “Generating Contrastive Snippets for Argument Search.” In Proceedings of the 9th International Conference on Computational Models of Argument, 21–31, 2022. http://dx.doi.org/10.3233/FAIA220138.","ama":"Alshomary M, Rieskamp J, Wachsmuth H. Generating Contrastive Snippets for Argument Search. In: Proceedings of the 9th International Conference on Computational Models of Argument. ; 2022:21-31. doi:http://dx.doi.org/10.3233/FAIA220138","apa":"Alshomary, M., Rieskamp, J., & Wachsmuth, H. (2022). Generating Contrastive Snippets for Argument Search. Proceedings of the 9th International Conference on Computational Models of Argument, 21–31. http://dx.doi.org/10.3233/FAIA220138","ieee":"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.","short":"M. Alshomary, J. Rieskamp, H. Wachsmuth, in: Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31."},"page":"21 - 31","doi":"http://dx.doi.org/10.3233/FAIA220138","_id":"32247","date_updated":"2022-12-06T10:25:25Z"},{"date_updated":"2022-05-09T14:58:39Z","_id":"31068","language":[{"iso":"eng"}],"year":"2022","citation":{"short":"M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.","ieee":"M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation structures of EFL learners from diverse language backgrounds,” 2022.","apa":"Chen, M.-H., Mudgal, G., Chen, W.-F., & Wachsmuth, H. (2022). Investigating the argumentation structures of EFL learners from diverse language backgrounds. EUROCALL.","ama":"Chen M-H, Mudgal G, Chen W-F, Wachsmuth H. Investigating the argumentation structures of EFL learners from diverse language backgrounds. In: EUROCALL. ; 2022.","chicago":"Chen, Mei-Hua, Garima Mudgal, Wei-Fan Chen, and Henning Wachsmuth. “Investigating the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.” In EUROCALL, 2022.","mla":"Chen, Mei-Hua, et al. “Investigating the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.” EUROCALL, 2022.","bibtex":"@inproceedings{Chen_Mudgal_Chen_Wachsmuth_2022, title={Investigating the argumentation structures of EFL learners from diverse language backgrounds}, booktitle={EUROCALL}, author={Chen, Mei-Hua and Mudgal, Garima and Chen, Wei-Fan and Wachsmuth, Henning}, year={2022} }"},"type":"conference_abstract","user_id":"82920","title":"Investigating the argumentation structures of EFL learners from diverse language backgrounds","author":[{"first_name":"Mei-Hua","full_name":"Chen, Mei-Hua","last_name":"Chen"},{"last_name":"Mudgal","first_name":"Garima","full_name":"Mudgal, Garima"},{"last_name":"Chen","id":"82920","first_name":"Wei-Fan","full_name":"Chen, Wei-Fan"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"}],"department":[{"_id":"600"}],"publication":"EUROCALL","status":"public","date_created":"2022-05-05T07:50:21Z","project":[{"_id":"1","name":"SFB 901: SFB 901"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - B1: SFB 901 - Subproject B1"}]},{"date_updated":"2023-05-02T13:25:45Z","_id":"29000","language":[{"iso":"eng"}],"supervisor":[{"full_name":"Kersting, Joschka","first_name":"Joschka","id":"58701","last_name":"Kersting"}],"citation":{"ieee":"M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing. 2022.","short":"M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing, 2022.","bibtex":"@book{Ahmed_2022, title={Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }","mla":"Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing. 2022.","chicago":"Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing, 2022.","ama":"Ahmed M. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing.; 2022.","apa":"Ahmed, M. (2022). Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing."},"type":"mastersthesis","year":"2022","abstract":[{"text":"This thesis aims to provide a bidirectional chatbot solution for the requirement engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide the composition of software service On-the-Fly (OTF). The sub-project (B1) of the SFB 901 project deals with the parameters of service configuration. OTF Computing aims to eradicate the dependency on the requirement engineers for the software development process. However, there is no existing bidirectional chatbot solution that analyses user software requirements and provides viable suggestions to the user regarding their service. Previously, CORDULA chatbot was developed to analyze the software requirements but cannot keep the conversation’s context. The Rasa framework is integrated with the knowledge base to solve the issue, the knowledge base provides domain-specific knowledge to the chatbot. The software description is passed through the natural language understanding process to give consciousness to the chatbot. This process involves various machine learning models, including app family classification, to correctly identify the domain for user OTF service. The statistical models like naïve Bayes, kNN and SVM are compared with transformer models for this classification task. Furthermore, the entities (functional requirements) are also separated from the user description.\r\nThe chatbot provides the suggestion of requirements from the preliminary service template with the support of the knowledge base. Furthermore, the generated response is compared with the state-of-the-art DialoGPT transformer model and ChatterBot conversational library. These models are trained over the software development related conversational dataset. All the responses are ranked using the DialoRPT model, and the BLEU score to evaluates the models’ responses. Moreover, the chatbot mod- els are tested with human participants, they used and scored the chatbot responses based on effectiveness, efficiency and satisfaction. The overall response accuracy is also measured by averaging the user approval over the generated responses.","lang":"eng"}],"user_id":"58701","title":"Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing","ddc":["004"],"file":[{"date_created":"2023-05-02T13:25:27Z","file_name":"Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf","access_level":"closed","file_size":3092211,"creator":"jkers","file_id":"44325","date_updated":"2023-05-02T13:25:27Z","content_type":"application/pdf","relation":"main_file","success":1}],"author":[{"first_name":"Mobeen","full_name":"Ahmed, Mobeen","last_name":"Ahmed"}],"department":[{"_id":"600"}],"file_date_updated":"2023-05-02T13:25:27Z","has_accepted_license":"1","status":"public","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"date_created":"2021-12-16T15:13:07Z","publication_status":"published"},{"type":"bachelorsthesis","year":"2022","citation":{"bibtex":"@book{Palushi_2022, title={Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }","mla":"Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks. 2022.","ama":"Palushi J. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks.; 2022.","apa":"Palushi, J. (2022). Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks.","chicago":"Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022.","ieee":"J. Palushi, Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks. 2022.","short":"J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022."},"language":[{"iso":"eng"}],"supervisor":[{"last_name":"Wachsmuth","id":"3900","first_name":"Henning","full_name":"Wachsmuth, Henning"}],"_id":"45790","date_updated":"2023-07-05T07:31:17Z","department":[{"_id":"600"}],"author":[{"last_name":"Palushi","full_name":"Palushi, Juela","first_name":"Juela"}],"date_created":"2023-06-27T12:57:57Z","project":[{"_id":"9","grant_number":"160364472","name":"SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)"},{"_id":"1","grant_number":"160364472","name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten "},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"}],"status":"public","title":"Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks","user_id":"477"},{"_id":"45789","date_updated":"2023-07-05T07:33:45Z","year":"2022","citation":{"short":"V. Budanurmath, Propaganda Technique Detection Using Connotation Frames, 2022.","ieee":"V. Budanurmath, Propaganda Technique Detection Using Connotation Frames. 2022.","apa":"Budanurmath, V. (2022). Propaganda Technique Detection Using Connotation Frames.","ama":"Budanurmath V. Propaganda Technique Detection Using Connotation Frames.; 2022.","chicago":"Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation Frames, 2022.","mla":"Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation Frames. 2022.","bibtex":"@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation Frames}, author={Budanurmath, Vinaykumar}, year={2022} }"},"type":"mastersthesis","supervisor":[{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"}],"language":[{"iso":"eng"}],"title":"Propaganda Technique Detection Using Connotation Frames","user_id":"477","date_created":"2023-06-27T12:56:04Z","project":[{"_id":"9","name":"SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)","grant_number":"160364472"},{"name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ","grant_number":"160364472","_id":"1"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"}],"status":"public","department":[{"_id":"600"}],"author":[{"last_name":"Budanurmath","first_name":"Vinaykumar","full_name":"Budanurmath, Vinaykumar"}]},{"author":[{"last_name":"Skitalinskaya","first_name":"Gabriella","full_name":"Skitalinskaya, Gabriella"},{"full_name":"Klaff, Jonas","first_name":"Jonas","last_name":"Klaff"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","id":"3900"}],"publication":"Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics","department":[{"_id":"600"}],"status":"public","date_created":"2020-10-16T12:39:27Z","user_id":"82920","title":"Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale","main_file_link":[{"url":"https://www.aclweb.org/anthology/2021.eacl-main.147/"}],"language":[{"iso":"eng"}],"citation":{"ieee":"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.","short":"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.","bibtex":"@inproceedings{Skitalinskaya_Klaff_Wachsmuth_2021, title={Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale}, booktitle={Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics}, author={Skitalinskaya, Gabriella and Klaff, Jonas and Wachsmuth, Henning}, year={2021}, pages={1718–1729} }","mla":"Skitalinskaya, Gabriella, et al. “Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale.” Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, 2021, pp. 1718–29.","ama":"Skitalinskaya G, Klaff J, Wachsmuth H. 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. ; 2021:1718-1729.","apa":"Skitalinskaya, G., Klaff, J., & Wachsmuth, H. (2021). 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 (pp. 1718–1729).","chicago":"Skitalinskaya, Gabriella, Jonas Klaff, and Henning 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, 1718–29, 2021."},"year":"2021","type":"conference","page":"1718-1729","_id":"20115","date_updated":"2022-01-06T06:54:19Z"},{"date_updated":"2022-01-06T06:59:35Z","_id":"3774","main_file_link":[{"url":"https://webis.de/downloads/publications/papers/bondarenko_2021.pdf"}],"page":"384-395","year":"2021","type":"conference","citation":{"ieee":"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.","short":"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.","bibtex":"@inproceedings{Bondarenko_Gienapp_Fröbe_Beloucif_Ajjour_Panchenko_Biemann_Stein_Wachsmuth_Potthast_et al._2021, title={Overview of Touché 2021: Argument Retrieval}, booktitle={Proceedings of the 43rd annual European Conference on Information Retrieval Research}, author={Bondarenko, Alexander and Gienapp, Lukas and Fröbe, Maik and Beloucif, Meriem and Ajjour, Yamen and Panchenko, Alexander and Biemann, Chris and Stein, Benno and Wachsmuth, Henning and Potthast, Martin and et al.}, year={2021}, pages={384–395} }","mla":"Bondarenko, Alexander, et al. “Overview of Touché 2021: Argument Retrieval.” Proceedings of the 43rd Annual European Conference on Information Retrieval Research, 2021, pp. 384–95.","ama":"Bondarenko A, Gienapp L, Fröbe M, et al. Overview of Touché 2021: Argument Retrieval. In: Proceedings of the 43rd Annual European Conference on Information Retrieval Research. ; 2021:384-395.","apa":"Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko, A., … Hagen, M. (2021). Overview of Touché 2021: Argument Retrieval. In Proceedings of the 43rd annual European Conference on Information Retrieval Research (pp. 384–395).","chicago":"Bondarenko, Alexander, Lukas Gienapp, Maik Fröbe, Meriem Beloucif, Yamen Ajjour, Alexander Panchenko, Chris Biemann, et al. “Overview of Touché 2021: Argument Retrieval.” In Proceedings of the 43rd Annual European Conference on Information Retrieval Research, 384–95, 2021."},"language":[{"iso":"eng"}],"title":"Overview of Touché 2021: Argument Retrieval","user_id":"82920","publication":"Proceedings of the 43rd annual European Conference on Information Retrieval Research","department":[{"_id":"600"}],"author":[{"full_name":"Bondarenko, Alexander","first_name":"Alexander","last_name":"Bondarenko"},{"last_name":"Gienapp","full_name":"Gienapp, Lukas","first_name":"Lukas"},{"first_name":"Maik","full_name":"Fröbe, Maik","last_name":"Fröbe"},{"last_name":"Beloucif","full_name":"Beloucif, Meriem","first_name":"Meriem"},{"last_name":"Ajjour","first_name":"Yamen","full_name":"Ajjour, Yamen"},{"full_name":"Panchenko, Alexander","first_name":"Alexander","last_name":"Panchenko"},{"first_name":"Chris","full_name":"Biemann, Chris","last_name":"Biemann"},{"first_name":"Benno","full_name":"Stein, Benno","last_name":"Stein"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","id":"3900"},{"last_name":"Potthast","full_name":"Potthast, Martin","first_name":"Martin"},{"last_name":"Hagen","first_name":"Matthias","full_name":"Hagen, Matthias"}],"date_created":"2018-08-02T11:40:53Z","status":"public"},{"oa":"1","_id":"23708","date_updated":"2022-01-06T06:55:58Z","language":[{"iso":"eng"}],"page":"165-175","citation":{"bibtex":"@inproceedings{Nouri_Gadiraju_Engels_Wachsmuth_2021, title={What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing}, booktitle={Proceedings of the 32nd ACM Conference on Hypertext and Social Media}, author={Nouri, Zahra and Gadiraju, Ujwal and Engels, Gregor and Wachsmuth, Henning}, year={2021}, pages={165–175} }","mla":"Nouri, Zahra, et al. “What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing.” Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 2021, pp. 165–75.","chicago":"Nouri, Zahra, Ujwal Gadiraju, Gregor Engels, and Henning Wachsmuth. “What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing.” In Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 165–75, 2021.","ama":"Nouri Z, Gadiraju U, Engels G, Wachsmuth H. What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing. In: Proceedings of the 32nd ACM Conference on Hypertext and Social Media. ; 2021:165-175.","apa":"Nouri, Z., Gadiraju, U., Engels, G., & Wachsmuth, H. (2021). What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing. Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 165–175.","ieee":"Z. Nouri, U. Gadiraju, G. Engels, and H. Wachsmuth, “What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing,” in Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 2021, pp. 165–175.","short":"Z. Nouri, U. Gadiraju, G. Engels, H. Wachsmuth, in: Proceedings of the 32nd ACM Conference on Hypertext and Social Media, 2021, pp. 165–175."},"year":"2021","type":"conference","main_file_link":[{"url":"https://dl.acm.org/doi/pdf/10.1145/3465336.3475109","open_access":"1"}],"user_id":"82920","title":"What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing","date_created":"2021-09-02T20:05:52Z","status":"public","publication":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","department":[{"_id":"600"}],"author":[{"last_name":"Nouri","id":"35802","first_name":"Zahra","full_name":"Nouri, Zahra"},{"last_name":"Gadiraju","full_name":"Gadiraju, Ujwal","first_name":"Ujwal"},{"full_name":"Engels, Gregor","first_name":"Gregor","id":"107","last_name":"Engels"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"}]},{"date_updated":"2022-01-06T06:55:28Z","_id":"22156","conference":{"start_date":"2021-08-19","name":"30th International Joint Conference on Artificial Intelligence (IJCAI-21)","location":"Online","end_date":"2021-08-26"},"doi":"10.24963/ijcai.2021/77","oa":"1","main_file_link":[{"open_access":"1","url":"https://www.ijcai.org/proceedings/2021/77"}],"citation":{"short":"M. Spliethöver, H. Wachsmuth, in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 2021, pp. 552–559.","ieee":"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.","ama":"Spliethöver M, Wachsmuth H. 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. ; 2021:552-559. doi:10.24963/ijcai.2021/77","apa":"Spliethöver, M., & Wachsmuth, H. (2021). Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 552–559. https://doi.org/10.24963/ijcai.2021/77","chicago":"Spliethöver, Maximilian, and Henning 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, 552–59, 2021. https://doi.org/10.24963/ijcai.2021/77.","bibtex":"@inproceedings{Spliethöver_Wachsmuth_2021, title={Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models}, DOI={10.24963/ijcai.2021/77}, booktitle={Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21}, author={Spliethöver, Maximilian and Wachsmuth, Henning}, year={2021}, pages={552–559} }","mla":"Spliethöver, Maximilian, and Henning Wachsmuth. “Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models.” Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 2021, pp. 552–59, doi:10.24963/ijcai.2021/77."},"type":"conference","year":"2021","page":"552-559","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Word embedding models reflect bias towards genders, ethnicities, and other social groups present in the underlying training data. Metrics such as ECT, RNSB, and WEAT quantify bias in these models based on predefined word lists representing social groups and bias-conveying concepts. How suitable these lists actually are to reveal bias - let alone the bias metrics in general - remains unclear, though. In this paper, we study how to assess the quality of bias metrics for word embedding models. In particular, we present a generic method, Bias Silhouette Analysis (BSA), that quantifies the accuracy and robustness of such a metric and of the word lists used. Given a biased and an unbiased reference embedding model, BSA applies the metric systematically for several subsets of the lists to the models. The variance and rate of convergence of the bias values of each model then entail the robustness of the word lists, whereas the distance between the models' values gives indications of the general accuracy of the metric with the word lists. We demonstrate the behavior of BSA on two standard embedding models for the three mentioned metrics with several word lists from existing research."}],"title":"Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models","user_id":"82920","author":[{"last_name":"Spliethöver","id":"84035","first_name":"Maximilian","orcid":"0000-0003-4364-1409","full_name":"Spliethöver, Maximilian"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","id":"3900"}],"quality_controlled":"1","publication":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21","department":[{"_id":"600"}],"status":"public","date_created":"2021-05-11T23:13:26Z"},{"_id":"22158","date_updated":"2022-01-06T06:55:28Z","oa":"1","main_file_link":[{"url":"https://aclanthology.org/2021.findings-acl.306.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"year":"2021","citation":{"chicago":"Syed, Shahbaz, Khalid Al-Khatib, Milad Alshomary, Henning Wachsmuth, and Martin 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, 3482–93, 2021.","ama":"Syed S, Al-Khatib K, Alshomary M, Wachsmuth H, Potthast M. 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. ; 2021:3482-3493.","apa":"Syed, S., Al-Khatib, K., Alshomary, M., Wachsmuth, H., & Potthast, M. (2021). Generating Informative Conclusions for Argumentative Texts. 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, 3482–3493.","bibtex":"@inproceedings{Syed_Al-Khatib_Alshomary_Wachsmuth_Potthast_2021, title={Generating Informative Conclusions for Argumentative Texts}, booktitle={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}, author={Syed, Shahbaz and Al-Khatib, Khalid and Alshomary, Milad and Wachsmuth, Henning and Potthast, Martin}, year={2021}, pages={3482–3493} }","mla":"Syed, Shahbaz, et al. “Generating Informative Conclusions for Argumentative Texts.” 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. 3482–93.","short":"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.","ieee":"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."},"type":"conference","page":"3482-3493","user_id":"82920","title":"Generating Informative Conclusions for Argumentative Texts","author":[{"full_name":"Syed, Shahbaz","first_name":"Shahbaz","last_name":"Syed"},{"last_name":"Al-Khatib","full_name":"Al-Khatib, Khalid","first_name":"Khalid"},{"id":"73059","last_name":"Alshomary","full_name":"Alshomary, Milad","first_name":"Milad"},{"full_name":"Wachsmuth, Henning","first_name":"Henning","id":"3900","last_name":"Wachsmuth"},{"last_name":"Potthast","first_name":"Martin","full_name":"Potthast, Martin"}],"department":[{"_id":"600"}],"publication":"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","status":"public","date_created":"2021-05-11T23:18:14Z"},{"language":[{"iso":"eng"}],"page":"1583-1595","year":"2021","type":"conference","citation":{"ieee":"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.","short":"J. Barrow, R. Jain, N. Lipka, F. Dernoncourt, V. Morariu, V. Manjunatha, D. Oard, P. Resnik, H. 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