[{"date_created":"2024-07-22T13:08:12Z","author":[{"last_name":"Sengupta","id":"99459","full_name":"Sengupta, Meghdut","first_name":"Meghdut"},{"full_name":"El Baff, Roxanne","last_name":"El Baff","first_name":"Roxanne"},{"first_name":"Milad","id":"73059","full_name":"Alshomary, Milad","last_name":"Alshomary"},{"first_name":"Henning","last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900"}],"publisher":"Association for Computational Linguistics","date_updated":"2024-07-26T13:02:57Z","title":"Analyzing the Use of Metaphors in News Editorials for Political Framing","page":"3621–3631","citation":{"ama":"Sengupta M, El Baff R, Alshomary M, Wachsmuth H. Analyzing the Use of Metaphors in News Editorials for Political Framing. In: Duh K, Gomez H, Bethard S, eds. <i>Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</i>. Association for Computational Linguistics; 2024:3621–3631.","ieee":"M. Sengupta, R. El Baff, M. Alshomary, and H. Wachsmuth, “Analyzing the Use of Metaphors in News Editorials for Political Framing,” in <i>Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</i>, 2024, pp. 3621–3631.","chicago":"Sengupta, Meghdut, Roxanne El Baff, Milad Alshomary, and Henning Wachsmuth. “Analyzing the Use of Metaphors in News Editorials for Political Framing.” In <i>Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</i>, edited by Kevin Duh, Helena Gomez, and Steven Bethard, 3621–3631. Mexico City, Mexico: Association for Computational Linguistics, 2024.","bibtex":"@inproceedings{Sengupta_El Baff_Alshomary_Wachsmuth_2024, place={Mexico City, Mexico}, title={Analyzing the Use of Metaphors in News Editorials for Political Framing}, booktitle={Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)}, publisher={Association for Computational Linguistics}, author={Sengupta, Meghdut and El Baff, Roxanne and Alshomary, Milad and Wachsmuth, Henning}, editor={Duh, Kevin and Gomez, Helena and Bethard, Steven}, year={2024}, pages={3621–3631} }","short":"M. Sengupta, R. El Baff, M. Alshomary, H. Wachsmuth, in: K. Duh, H. Gomez, S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Association for Computational Linguistics, Mexico City, Mexico, 2024, pp. 3621–3631.","mla":"Sengupta, Meghdut, et al. “Analyzing the Use of Metaphors in News Editorials for Political Framing.” <i>Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</i>, edited by Kevin Duh et al., Association for Computational Linguistics, 2024, pp. 3621–3631.","apa":"Sengupta, M., El Baff, R., Alshomary, M., &#38; Wachsmuth, H. (2024). Analyzing the Use of Metaphors in News Editorials for Political Framing. In K. Duh, H. Gomez, &#38; S. Bethard (Eds.), <i>Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</i> (pp. 3621–3631). Association for Computational Linguistics."},"year":"2024","place":"Mexico City, Mexico","department":[{"_id":"600"},{"_id":"660"}],"user_id":"3900","_id":"55338","project":[{"_id":"127","name":"TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens"}],"language":[{"iso":"eng"}],"publication":"Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)","type":"conference","status":"public","editor":[{"first_name":"Kevin","last_name":"Duh","full_name":"Duh, Kevin"},{"first_name":"Helena","full_name":"Gomez, Helena","last_name":"Gomez"},{"first_name":"Steven","last_name":"Bethard","full_name":"Bethard, Steven"}],"abstract":[{"lang":"eng","text":"Metaphorical language is a pivotal element inthe realm of political framing. Existing workfrom linguistics and the social sciences providescompelling evidence regarding the distinctivenessof conceptual framing for politicalideology perspectives. However, the nature andutilization of metaphors and the effect on audiencesof different political ideologies withinpolitical discourses are hardly explored. Toenable research in this direction, in this workwe create a dataset, originally based on newseditorials and labeled with their persuasive effectson liberals and conservatives and extend itwith annotations pertaining to metaphorical usageof language. To that end, first, we identifyall single metaphors and composite metaphors.Secondly, we provide annotations of the sourceand target domains for each metaphor. As aresult, our corpus consists of 300 news editorialsannotated with spans of texts containingmetaphors and the corresponding domains ofwhich these metaphors draw from. Our analysisshows that liberal readers are affected bymetaphors, whereas conservatives are resistantto them. Both ideologies are affected differentlybased on the metaphor source and targetcategory. For example, liberals are affected bymetaphors in the Darkness {&} Light (e.g., death)source domains, where as the source domain ofNature affects conservatives more significantly."}]},{"publication":"Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)","type":"conference","abstract":[{"lang":"eng","text":"Explanations are pervasive in our lives. Mostly, they occur in dialogical form where an explainer discusses a concept or phenomenon of interest with an explainee. Leaving the explainee with a clear understanding is not straightforward due to the knowledge gap between the two participants. Previous research looked at the interaction of explanation moves, dialogue acts, and topics in successful dialogues with expert explainers. However, daily-life explanations often fail, raising the question of what makes a dialogue successful. In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee{’}s side. In particular, we first construct a corpus of 399 dialogues from the Reddit forum {Explain Like I am Five} and annotate it for interaction flows and explanation quality. We then analyze the interaction flows, comparing them to those appearing in expert dialogues. Finally, we encode the interaction flows using two language models that can handle long inputs, and we provide empirical evidence for the effectiveness boost gained through the encoding in predicting the success of explanation dialogues."}],"editor":[{"full_name":"Calzolari, Nicoletta","last_name":"Calzolari","first_name":"Nicoletta"},{"last_name":"Kan","full_name":"Kan, Min-Yen","first_name":"Min-Yen"},{"first_name":"Veronique","full_name":"Hoste, Veronique","last_name":"Hoste"},{"first_name":"Alessandro","last_name":"Lenci","full_name":"Lenci, Alessandro"},{"last_name":"Sakti","full_name":"Sakti, Sakriani","first_name":"Sakriani"},{"first_name":"Nianwen","full_name":"Xue, Nianwen","last_name":"Xue"}],"status":"public","_id":"55404","project":[{"name":"TRR 318 - INF: TRR 318 - Project Area INF","_id":"118"}],"department":[{"_id":"600"},{"_id":"660"}],"user_id":"67893","language":[{"iso":"eng"}],"quality_controlled":"1","year":"2024","place":"Torino, Italia","page":"11523–11536","citation":{"ieee":"M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, and H. Wachsmuth, “Modeling the Quality of Dialogical Explanations,” in <i>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</i>, 2024, pp. 11523–11536.","chicago":"Alshomary, Milad, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp Cimiano, and Henning Wachsmuth. “Modeling the Quality of Dialogical Explanations.” In <i>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</i>, edited by Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, and Nianwen Xue, 11523–11536. Torino, Italia: ELRA and ICCL, 2024.","ama":"Alshomary M, Lange F, Booshehri M, Sengupta M, Cimiano P, Wachsmuth H. Modeling the Quality of Dialogical Explanations. In: Calzolari N, Kan M-Y, Hoste V, Lenci A, Sakti S, Xue N, eds. <i>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</i>. ELRA and ICCL; 2024:11523–11536.","apa":"Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., &#38; Wachsmuth, H. (2024). Modeling the Quality of Dialogical Explanations. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, &#38; N. Xue (Eds.), <i>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</i> (pp. 11523–11536). ELRA and ICCL.","mla":"Alshomary, Milad, et al. “Modeling the Quality of Dialogical Explanations.” <i>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</i>, edited by Nicoletta Calzolari et al., ELRA and ICCL, 2024, pp. 11523–11536.","bibtex":"@inproceedings{Alshomary_Lange_Booshehri_Sengupta_Cimiano_Wachsmuth_2024, place={Torino, Italia}, title={Modeling the Quality of Dialogical Explanations}, booktitle={Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}, publisher={ELRA and ICCL}, author={Alshomary, Milad and Lange, Felix and Booshehri, Meisam and Sengupta, Meghdut and Cimiano, Philipp and Wachsmuth, Henning}, editor={Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen}, year={2024}, pages={11523–11536} }","short":"M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, H. Wachsmuth, in: N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, Torino, Italia, 2024, pp. 11523–11536."},"date_updated":"2024-12-17T11:30:25Z","publisher":"ELRA and ICCL","date_created":"2024-07-26T13:04:25Z","author":[{"full_name":"Alshomary, Milad","id":"73059","last_name":"Alshomary","first_name":"Milad"},{"id":"67893","full_name":"Lange, Felix","last_name":"Lange","first_name":"Felix"},{"last_name":"Booshehri","full_name":"Booshehri, Meisam","first_name":"Meisam"},{"first_name":"Meghdut","full_name":"Sengupta, Meghdut","id":"99459","last_name":"Sengupta"},{"last_name":"Cimiano","full_name":"Cimiano, Philipp","first_name":"Philipp"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","id":"3900","last_name":"Wachsmuth"}],"title":"Modeling the Quality of Dialogical Explanations"},{"department":[{"_id":"600"},{"_id":"660"}],"user_id":"84035","_id":"58722","project":[{"_id":"118","name":"TRR 318 - INF: TRR 318 - Project Area INF"}],"language":[{"iso":"eng"}],"publication":"Findings of the Association for Computational Linguistics: ACL 2024","type":"conference","status":"public","abstract":[{"lang":"eng","text":"Dialects introduce syntactic and lexical variations in language that occur in regional or social groups. Most NLP methods are not sensitive to such variations. This may lead to unfair behavior of the methods, conveying negative bias towards dialect speakers. While previous work has studied dialect-related fairness for aspects like hate speech, other aspects of biased language, such as lewdness, remain fully unexplored. To fill this gap, we investigate performance disparities between dialects in the detection of five aspects of biased language and how to mitigate them. To alleviate bias, we present a multitask learning approach that models dialect language as an auxiliary task to incorporate syntactic and lexical variations. In our experiments with African-American English dialect, we provide empirical evidence that complementing common learning approaches with dialect modeling improves their fairness. Furthermore, the results suggest that multitask learning achieves state-of-the-art performance and helps to detect properties of biased language more reliably."}],"editor":[{"last_name":"Ku","full_name":"Ku, Lun-Wei","first_name":"Lun-Wei"},{"first_name":"Andre","full_name":"Martins, Andre","last_name":"Martins"},{"first_name":"Vivek","full_name":"Srikumar, Vivek","last_name":"Srikumar"}],"date_created":"2025-02-20T08:18:01Z","author":[{"first_name":"Maximilian","full_name":"Spliethöver, Maximilian","id":"84035","orcid":"0000-0003-4364-1409","last_name":"Spliethöver"},{"first_name":"Sai Nikhil","full_name":"Menon, Sai Nikhil","last_name":"Menon"},{"last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900","first_name":"Henning"}],"oa":"1","date_updated":"2025-09-12T09:52:59Z","publisher":"Association for Computational Linguistics","doi":"10.18653/v1/2024.findings-acl.553","main_file_link":[{"open_access":"1","url":"https://aclanthology.org/2024.findings-acl.553/"}],"title":"Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness","related_material":{"link":[{"url":"https://github.com/webis-de/acl24-dialect-aware-bias-detection","relation":"software"}]},"page":"9294–9313","citation":{"ama":"Spliethöver M, Menon SN, Wachsmuth H. Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness. In: Ku L-W, Martins A, Srikumar V, eds. <i>Findings of the Association for Computational Linguistics: ACL 2024</i>. Association for Computational Linguistics; 2024:9294–9313. doi:<a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">10.18653/v1/2024.findings-acl.553</a>","chicago":"Spliethöver, Maximilian, Sai Nikhil Menon, and Henning Wachsmuth. “Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness.” In <i>Findings of the Association for Computational Linguistics: ACL 2024</i>, edited by Lun-Wei Ku, Andre Martins, and Vivek Srikumar, 9294–9313. Bangkok, Thailand: Association for Computational Linguistics, 2024. <a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">https://doi.org/10.18653/v1/2024.findings-acl.553</a>.","ieee":"M. Spliethöver, S. N. Menon, and H. Wachsmuth, “Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness,” in <i>Findings of the Association for Computational Linguistics: ACL 2024</i>, 2024, pp. 9294–9313, doi: <a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">10.18653/v1/2024.findings-acl.553</a>.","bibtex":"@inproceedings{Spliethöver_Menon_Wachsmuth_2024, place={Bangkok, Thailand}, title={Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness}, DOI={<a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">10.18653/v1/2024.findings-acl.553</a>}, booktitle={Findings of the Association for Computational Linguistics: ACL 2024}, publisher={Association for Computational Linguistics}, author={Spliethöver, Maximilian and Menon, Sai Nikhil and Wachsmuth, Henning}, editor={Ku, Lun-Wei and Martins, Andre and Srikumar, Vivek}, year={2024}, pages={9294–9313} }","mla":"Spliethöver, Maximilian, et al. “Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness.” <i>Findings of the Association for Computational Linguistics: ACL 2024</i>, edited by Lun-Wei Ku et al., Association for Computational Linguistics, 2024, pp. 9294–9313, doi:<a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">10.18653/v1/2024.findings-acl.553</a>.","short":"M. Spliethöver, S.N. Menon, H. Wachsmuth, in: L.-W. Ku, A. Martins, V. Srikumar (Eds.), Findings of the Association for Computational Linguistics: ACL 2024, Association for Computational Linguistics, Bangkok, Thailand, 2024, pp. 9294–9313.","apa":"Spliethöver, M., Menon, S. N., &#38; Wachsmuth, H. (2024). Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness. In L.-W. Ku, A. Martins, &#38; V. Srikumar (Eds.), <i>Findings of the Association for Computational Linguistics: ACL 2024</i> (pp. 9294–9313). Association for Computational Linguistics. <a href=\"https://doi.org/10.18653/v1/2024.findings-acl.553\">https://doi.org/10.18653/v1/2024.findings-acl.553</a>"},"place":"Bangkok, Thailand","year":"2024"},{"doi":"10.18653/v1/2023.findings-emnlp.308","title":"Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms","date_created":"2024-07-26T13:09:20Z","author":[{"first_name":"Meghdut","id":"99459","full_name":"Sengupta, Meghdut","last_name":"Sengupta"},{"full_name":"Alshomary, Milad","id":"73059","last_name":"Alshomary","first_name":"Milad"},{"first_name":"Ingrid","id":"451","full_name":"Scharlau, Ingrid","last_name":"Scharlau","orcid":"0000-0003-2364-9489"},{"last_name":"Wachsmuth","id":"3900","full_name":"Wachsmuth, Henning","first_name":"Henning"}],"publisher":"Association for Computational Linguistics","date_updated":"2024-07-26T13:19:53Z","citation":{"apa":"Sengupta, M., Alshomary, M., Scharlau, I., &#38; Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In H. Bouamor, J. Pino, &#38; K. Bali (Eds.), <i>Findings of the Association for Computational Linguistics: EMNLP 2023</i> (pp. 4636–4659). Association for Computational Linguistics. <a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">https://doi.org/10.18653/v1/2023.findings-emnlp.308</a>","mla":"Sengupta, Meghdut, et al. “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms.” <i>Findings of the Association for Computational Linguistics: EMNLP 2023</i>, edited by Houda Bouamor et al., Association for Computational Linguistics, 2023, pp. 4636–4659, doi:<a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">10.18653/v1/2023.findings-emnlp.308</a>.","bibtex":"@inproceedings{Sengupta_Alshomary_Scharlau_Wachsmuth_2023, place={Singapore}, title={Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms}, DOI={<a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">10.18653/v1/2023.findings-emnlp.308</a>}, booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023}, publisher={Association for Computational Linguistics}, author={Sengupta, Meghdut and Alshomary, Milad and Scharlau, Ingrid and Wachsmuth, Henning}, editor={Bouamor, Houda and Pino, Juan and Bali, Kalika}, year={2023}, pages={4636–4659} }","short":"M. Sengupta, M. Alshomary, I. Scharlau, H. Wachsmuth, in: H. Bouamor, J. Pino, K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023, Association for Computational Linguistics, Singapore, 2023, pp. 4636–4659.","ama":"Sengupta M, Alshomary M, Scharlau I, Wachsmuth H. Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In: Bouamor H, Pino J, Bali K, eds. <i>Findings of the Association for Computational Linguistics: EMNLP 2023</i>. Association for Computational Linguistics; 2023:4636–4659. doi:<a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">10.18653/v1/2023.findings-emnlp.308</a>","chicago":"Sengupta, Meghdut, Milad Alshomary, Ingrid Scharlau, and Henning Wachsmuth. “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms.” In <i>Findings of the Association for Computational Linguistics: EMNLP 2023</i>, edited by Houda Bouamor, Juan Pino, and Kalika Bali, 4636–4659. Singapore: Association for Computational Linguistics, 2023. <a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">https://doi.org/10.18653/v1/2023.findings-emnlp.308</a>.","ieee":"M. Sengupta, M. Alshomary, I. Scharlau, and H. Wachsmuth, “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms,” in <i>Findings of the Association for Computational Linguistics: EMNLP 2023</i>, 2023, pp. 4636–4659, doi: <a href=\"https://doi.org/10.18653/v1/2023.findings-emnlp.308\">10.18653/v1/2023.findings-emnlp.308</a>."},"page":"4636–4659","place":"Singapore","year":"2023","language":[{"iso":"eng"}],"user_id":"3900","department":[{"_id":"600"},{"_id":"660"}],"project":[{"name":"TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens","_id":"127"}],"_id":"55406","status":"public","abstract":[{"text":"Metaphorical language, such as {“}spending time together{”}, projects meaning from a source domain (here, $money$) to a target domain ($time$). Thereby, it highlights certain aspects of the target domain, such as the $effort$ behind the time investment. Highlighting aspects with metaphors (while hiding others) bridges the two domains and is the core of metaphorical meaning construction. For metaphor interpretation, linguistic theories stress that identifying the highlighted aspects is important for a better understanding of metaphors. However, metaphor research in NLP has not yet dealt with the phenomenon of highlighting. In this paper, we introduce the task of identifying the main aspect highlighted in a metaphorical sentence. Given the inherent interaction of source domains and highlighted aspects, we propose two multitask approaches - a joint learning approach and a continual learning approach - based on a finetuned contrastive learning model to jointly predict highlighted aspects and source domains. We further investigate whether (predicted) information about a source domain leads to better performance in predicting the highlighted aspects, and vice versa. Our experiments on an existing corpus suggest that, with the corresponding information, the performance to predict the other improves in terms of model accuracy in predicting highlighted aspects and source domains notably compared to the single-task baselines.","lang":"eng"}],"editor":[{"last_name":"Bouamor","full_name":"Bouamor, Houda","first_name":"Houda"},{"first_name":"Juan","last_name":"Pino","full_name":"Pino, Juan"},{"last_name":"Bali","full_name":"Bali, Kalika","first_name":"Kalika"}],"type":"conference","publication":"Findings of the Association for Computational Linguistics: EMNLP 2023"},{"publication":"Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics","type":"conference","status":"public","abstract":[{"text":"In real-world debates, the most common way to counter an argument is to reason against its main point, that is, its conclusion. Existing work on the automatic generation of natural language counter-arguments does not address the relation to the conclusion, possibly because many arguments leave their conclusion implicit. In this paper, we hypothesize that the key to effective counter-argument generation is to explicitly model the argument‘s conclusion and to ensure that the stance of the generated counter is opposite to that conclusion. In particular, we propose a multitask approach that jointly learns to generate both the conclusion and the counter of an input argument. The approach employs a stance-based ranking component that selects the counter from a diverse set of generated candidates whose stance best opposes the generated conclusion. In both automatic and manual evaluation, we provide evidence that our approach generates more relevant and stance-adhering counters than strong baselines.","lang":"eng"}],"editor":[{"full_name":"Vlachos, Andreas","last_name":"Vlachos","first_name":"Andreas"},{"last_name":"Augenstein","full_name":"Augenstein, Isabelle","first_name":"Isabelle"}],"department":[{"_id":"600"},{"_id":"660"}],"user_id":"3900","_id":"58723","project":[{"_id":"118","name":"TRR 318 - INF: TRR 318 - Project Area INF"}],"language":[{"iso":"eng"}],"page":"957–967","citation":{"ieee":"M. Alshomary and H. Wachsmuth, “Conclusion-based Counter-Argument Generation,” in <i>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</i>, 2023, pp. 957–967, doi: <a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">10.18653/v1/2023.eacl-main.67</a>.","chicago":"Alshomary, Milad, and Henning Wachsmuth. “Conclusion-Based Counter-Argument Generation.” In <i>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</i>, edited by Andreas Vlachos and Isabelle Augenstein, 957–967. Dubrovnik, Croatia: Association for Computational Linguistics, 2023. <a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">https://doi.org/10.18653/v1/2023.eacl-main.67</a>.","ama":"Alshomary M, Wachsmuth H. Conclusion-based Counter-Argument Generation. In: Vlachos A, Augenstein I, eds. <i>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</i>. Association for Computational Linguistics; 2023:957–967. doi:<a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">10.18653/v1/2023.eacl-main.67</a>","apa":"Alshomary, M., &#38; Wachsmuth, H. (2023). Conclusion-based Counter-Argument Generation. In A. Vlachos &#38; I. Augenstein (Eds.), <i>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</i> (pp. 957–967). Association for Computational Linguistics. <a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">https://doi.org/10.18653/v1/2023.eacl-main.67</a>","bibtex":"@inproceedings{Alshomary_Wachsmuth_2023, place={Dubrovnik, Croatia}, title={Conclusion-based Counter-Argument Generation}, DOI={<a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">10.18653/v1/2023.eacl-main.67</a>}, booktitle={Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics}, publisher={Association for Computational Linguistics}, author={Alshomary, Milad and Wachsmuth, Henning}, editor={Vlachos, Andreas and Augenstein, Isabelle}, year={2023}, pages={957–967} }","mla":"Alshomary, Milad, and Henning Wachsmuth. “Conclusion-Based Counter-Argument Generation.” <i>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics</i>, edited by Andreas Vlachos and Isabelle Augenstein, Association for Computational Linguistics, 2023, pp. 957–967, doi:<a href=\"https://doi.org/10.18653/v1/2023.eacl-main.67\">10.18653/v1/2023.eacl-main.67</a>.","short":"M. Alshomary, H. Wachsmuth, in: A. Vlachos, I. Augenstein (Eds.), Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, Dubrovnik, Croatia, 2023, pp. 957–967."},"place":"Dubrovnik, Croatia","year":"2023","author":[{"last_name":"Alshomary","full_name":"Alshomary, Milad","id":"73059","first_name":"Milad"},{"last_name":"Wachsmuth","id":"3900","full_name":"Wachsmuth, Henning","first_name":"Henning"}],"date_created":"2025-02-20T08:20:35Z","date_updated":"2025-02-20T08:21:41Z","publisher":"Association for Computational Linguistics","doi":"10.18653/v1/2023.eacl-main.67","title":"Conclusion-based Counter-Argument Generation"},{"type":"conference","publication":"Proceedings of the 29th International Conference on Computational Linguistics","status":"public","_id":"33004","user_id":"82920","department":[{"_id":"600"}],"language":[{"iso":"eng"}],"year":"2022","citation":{"ieee":"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 <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2022, pp. 344–354.","chicago":"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.” In <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 344–54, 2022.","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. In: <i>Proceedings of the 29th International Conference on Computational Linguistics</i>. ; 2022:344-354.","apa":"Wachsmuth, H., &#38; Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning How to Explain. <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 344–354.","short":"H. Wachsmuth, M. Alshomary, in: Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.","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.” <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 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} }"},"page":"344 - 354","date_updated":"2022-11-10T09:06:39Z","author":[{"id":"3900","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","first_name":"Henning"},{"last_name":"Alshomary","full_name":"Alshomary, Milad","id":"73059","first_name":"Milad"}],"date_created":"2022-08-18T10:00:46Z","title":"\"Mama Always Had a Way of Explaining Things So I Could Understand\": A Dialogue Corpus for Learning How to Explain"},{"title":"On the Role of Knowledge in  Computational Argumentation","date_created":"2022-11-10T08:39:38Z","author":[{"first_name":"Anne","last_name":"Lauscher","full_name":"Lauscher, Anne"},{"first_name":"Henning","last_name":"Wachsmuth","id":"3900","full_name":"Wachsmuth, Henning"},{"last_name":"Gurevych","full_name":"Gurevych, Iryna","first_name":"Iryna"},{"last_name":"Glavaš","full_name":"Glavaš, Goran","first_name":"Goran"}],"date_updated":"2022-11-10T08:39:48Z","citation":{"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.” <i>Transactions of the Association for Computational Linguistics</i>, 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., &#38; Glavaš, G. (2022). On the Role of Knowledge in  Computational Argumentation. <i>Transactions of the Association for Computational Linguistics</i>.","chicago":"Lauscher, Anne, Henning Wachsmuth, Iryna Gurevych, and Goran Glavaš. “On the Role of Knowledge in  Computational Argumentation.” <i>Transactions of the Association for Computational Linguistics</i>, 2022.","ieee":"A. Lauscher, H. Wachsmuth, I. Gurevych, and G. Glavaš, “On the Role of Knowledge in  Computational Argumentation,” <i>Transactions of the Association for Computational Linguistics</i>, 2022.","ama":"Lauscher A, Wachsmuth H, Gurevych I, Glavaš G. On the Role of Knowledge in  Computational Argumentation. <i>Transactions of the Association for Computational Linguistics</i>. Published online 2022."},"year":"2022","language":[{"iso":"eng"}],"department":[{"_id":"600"}],"user_id":"82920","_id":"34049","status":"public","publication":"Transactions of the Association for Computational Linguistics","type":"journal_article"},{"language":[{"iso":"eng"}],"_id":"22157","department":[{"_id":"600"}],"user_id":"82920","status":"public","publication":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics","type":"conference","title":"Identifying the Human Values behind Arguments","date_updated":"2022-11-10T09:09:27Z","date_created":"2021-05-11T23:15:42Z","author":[{"first_name":"Johannes","last_name":"Kiesel","full_name":"Kiesel, Johannes"},{"first_name":"Milad","id":"73059","full_name":"Alshomary, Milad","last_name":"Alshomary"},{"last_name":"Handke","full_name":"Handke, Nicolas","first_name":"Nicolas"},{"first_name":"Xiaoni","last_name":"Cai","full_name":"Cai, Xiaoni"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","id":"3900","last_name":"Wachsmuth"},{"last_name":"Stein","full_name":"Stein, Benno","first_name":"Benno"}],"year":"2022","page":"4459 - 4471","citation":{"ieee":"J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, and B. Stein, “Identifying the Human Values behind Arguments,” in <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 2022, pp. 4459–4471.","chicago":"Kiesel, Johannes, Milad Alshomary, Nicolas Handke, Xiaoni Cai, Henning Wachsmuth, and Benno Stein. “Identifying the Human Values behind Arguments.” In <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 4459–71, 2022.","ama":"Kiesel J, Alshomary M, Handke N, Cai X, Wachsmuth H, Stein B. Identifying the Human Values behind Arguments. In: <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>. ; 2022:4459-4471.","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.","mla":"Kiesel, Johannes, et al. “Identifying the Human Values behind Arguments.” <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 2022, pp. 4459–71.","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} }","apa":"Kiesel, J., Alshomary, M., Handke, N., Cai, X., Wachsmuth, H., &#38; Stein, B. (2022). Identifying the Human Values behind Arguments. <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 4459–4471."}},{"publication":"Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)","type":"conference","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"}],"status":"public","external_id":{"arxiv":["2211.03634"]},"_id":"34047","department":[{"_id":"600"}],"user_id":"84035","extern":"1","language":[{"iso":"eng"}],"year":"2022","citation":{"mla":"Spliethöver, Maximilian, et al. “No Word Embedding Model Is Perfect: Evaluating the Representation  Accuracy for Social Bias in the Media.” <i>Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)</i>, 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.","apa":"Spliethöver, M., Keiff, M., &#38; Wachsmuth, H. (2022). No Word Embedding Model Is Perfect: Evaluating the Representation  Accuracy for Social Bias in the Media. <i>Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)</i>. The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi.","ama":"Spliethöver M, Keiff M, Wachsmuth H. No Word Embedding Model Is Perfect: Evaluating the Representation  Accuracy for Social Bias in the Media. In: <i>Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)</i>. Association for Computational Linguistics; 2022.","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 <i>Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)</i>. Association for Computational Linguistics, 2022.","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."},"publisher":"Association for Computational Linguistics","date_updated":"2022-11-11T12:49:47Z","date_created":"2022-11-10T08:28:53Z","author":[{"full_name":"Spliethöver, Maximilian","last_name":"Spliethöver","first_name":"Maximilian"},{"last_name":"Keiff","full_name":"Keiff, Maximilian","first_name":"Maximilian"},{"first_name":"Henning","last_name":"Wachsmuth","full_name":"Wachsmuth, Henning"}],"title":"No Word Embedding Model Is Perfect: Evaluating the Representation  Accuracy for Social Bias in the Media","conference":{"start_date":"2022-12-07","name":"The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)","location":"Abu Dhabi","end_date":"2022-12-11"}},{"_id":"34077","user_id":"52174","department":[{"_id":"600"}],"alternative_title":["Extended Abstract"],"type":"book_chapter","publication":"Lecture Notes in Computer Science","status":"public","publisher":"Springer International Publishing","date_updated":"2022-11-14T13:48:38Z","date_created":"2022-11-14T13:47:51Z","author":[{"first_name":"Alexander","full_name":"Bondarenko, Alexander","last_name":"Bondarenko"},{"full_name":"Fröbe, Maik","last_name":"Fröbe","first_name":"Maik"},{"last_name":"Kiesel","full_name":"Kiesel, Johannes","first_name":"Johannes"},{"first_name":"Shahbaz","full_name":"Syed, Shahbaz","last_name":"Syed"},{"last_name":"Gurcke","full_name":"Gurcke, Timon","first_name":"Timon"},{"first_name":"Meriem","full_name":"Beloucif, Meriem","last_name":"Beloucif"},{"first_name":"Alexander","last_name":"Panchenko","full_name":"Panchenko, Alexander"},{"first_name":"Chris","full_name":"Biemann, Chris","last_name":"Biemann"},{"full_name":"Stein, Benno","last_name":"Stein","first_name":"Benno"},{"full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","first_name":"Henning"},{"last_name":"Potthast","full_name":"Potthast, Martin","first_name":"Martin"},{"first_name":"Matthias","full_name":"Hagen, Matthias","last_name":"Hagen"}],"title":"Overview of Touché 2022: Argument Retrieval","doi":"10.1007/978-3-030-99739-7_43","publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783030997380","9783030997397"]},"place":"Cham","year":"2022","citation":{"chicago":"Bondarenko, Alexander, Maik Fröbe, Johannes Kiesel, Shahbaz Syed, Timon Gurcke, Meriem Beloucif, Alexander Panchenko, et al. “Overview of Touché 2022: Argument Retrieval.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-030-99739-7_43\">https://doi.org/10.1007/978-3-030-99739-7_43</a>.","ieee":"A. Bondarenko <i>et al.</i>, “Overview of Touché 2022: Argument Retrieval,” in <i>Lecture Notes in Computer Science</i>, Cham: Springer International Publishing, 2022.","ama":"Bondarenko A, Fröbe M, Kiesel J, et al. Overview of Touché 2022: Argument Retrieval. In: <i>Lecture Notes in Computer Science</i>. Springer International Publishing; 2022. doi:<a href=\"https://doi.org/10.1007/978-3-030-99739-7_43\">10.1007/978-3-030-99739-7_43</a>","apa":"Bondarenko, A., Fröbe, M., Kiesel, J., Syed, S., Gurcke, T., Beloucif, M., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., &#38; Hagen, M. (2022). Overview of Touché 2022: Argument Retrieval. In <i>Lecture Notes in Computer Science</i>. Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-030-99739-7_43\">https://doi.org/10.1007/978-3-030-99739-7_43</a>","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={<a href=\"https://doi.org/10.1007/978-3-030-99739-7_43\">10.1007/978-3-030-99739-7_43</a>}, 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} }","mla":"Bondarenko, Alexander, et al. “Overview of Touché 2022: Argument Retrieval.” <i>Lecture Notes in Computer Science</i>, Springer International Publishing, 2022, doi:<a href=\"https://doi.org/10.1007/978-3-030-99739-7_43\">10.1007/978-3-030-99739-7_43</a>.","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."}},{"publication":"Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)","type":"conference","status":"public","_id":"33274","project":[{"_id":"9","name":"SFB 901 - B1: SFB 901 - Subproject B1"},{"name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"}],"department":[{"_id":"600"}],"user_id":"477","language":[{"iso":"eng"}],"year":"2022","page":"51 - 61","citation":{"apa":"Chen, W.-F., Chen, M.-H., Mudgal, G., &#38; Wachsmuth, H. (2022). Analyzing Culture-Specific Argument Structures in Learner Essays. <i>Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)</i>, 51–61.","mla":"Chen, Wei-Fan, et al. “Analyzing Culture-Specific Argument Structures in Learner Essays.” <i>Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)</i>, 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} }","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.","chicago":"Chen, Wei-Fan, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. “Analyzing Culture-Specific Argument Structures in Learner Essays.” In <i>Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)</i>, 51–61, 2022.","ieee":"W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific Argument Structures in Learner Essays,” in <i>Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)</i>, 2022, pp. 51–61.","ama":"Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument Structures in Learner Essays. In: <i>Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)</i>. ; 2022:51-61."},"date_updated":"2022-11-18T09:56:17Z","date_created":"2022-09-06T13:51:23Z","author":[{"first_name":"Wei-Fan","full_name":"Chen, Wei-Fan","id":"82920","last_name":"Chen"},{"first_name":"Mei-Hua","full_name":"Chen, Mei-Hua","last_name":"Chen"},{"last_name":"Mudgal","full_name":"Mudgal, Garima","first_name":"Garima"},{"first_name":"Henning","full_name":"Wachsmuth, Henning","id":"3900","last_name":"Wachsmuth"}],"title":"Analyzing Culture-Specific Argument Structures in Learner Essays"},{"status":"public","type":"conference_abstract","publication":"EUROCALL","language":[{"iso":"eng"}],"project":[{"name":"SFB 901: SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"},{"name":"SFB 901 - B1: SFB 901 - Subproject B1","_id":"9"}],"_id":"31068","user_id":"82920","department":[{"_id":"600"}],"year":"2022","citation":{"apa":"Chen, M.-H., Mudgal, G., Chen, W.-F., &#38; Wachsmuth, H. (2022). Investigating the argumentation structures of EFL learners from diverse language backgrounds. <i>EUROCALL</i>.","mla":"Chen, Mei-Hua, et al. “Investigating the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.” <i>EUROCALL</i>, 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} }","short":"M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, 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 <i>EUROCALL</i>, 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.","ama":"Chen M-H, Mudgal G, Chen W-F, Wachsmuth H. Investigating the argumentation structures of EFL learners from diverse language backgrounds. In: <i>EUROCALL</i>. ; 2022."},"title":"Investigating the argumentation structures of EFL learners from diverse language backgrounds","date_updated":"2022-05-09T14:58:39Z","date_created":"2022-05-05T07:50:21Z","author":[{"full_name":"Chen, Mei-Hua","last_name":"Chen","first_name":"Mei-Hua"},{"first_name":"Garima","full_name":"Mudgal, Garima","last_name":"Mudgal"},{"first_name":"Wei-Fan","last_name":"Chen","id":"82920","full_name":"Chen, Wei-Fan"},{"last_name":"Wachsmuth","id":"3900","full_name":"Wachsmuth, Henning","first_name":"Henning"}]},{"abstract":[{"text":"As AI is more and more pervasive in everyday life, humans have an increasing demand to understand its behavior and decisions. Most research on explainable AI builds on the premise that there is one ideal explanation to be found. In fact, however, everyday explanations are co-constructed in a dialogue between the person explaining (the explainer) and the specific person being explained to (the explainee). In this paper, we introduce a first corpus of dialogical explanations to enable NLP research on how humans explain as well as on how AI can learn to imitate this process. The corpus consists of 65 transcribed English dialogues from the Wired video series 5 Levels, explaining 13 topics to five explainees of different proficiency. All 1550 dialogue turns have been manually labeled by five independent professionals for the topic discussed as well as for the dialogue act and the explanation move performed. We analyze linguistic patterns of explainers and explainees, and we explore differences across proficiency levels. BERT-based baseline results indicate that sequence information helps predicting topics, acts, and moves effectively.","lang":"eng"}],"editor":[{"first_name":"Nicoletta","full_name":"Calzolari, Nicoletta","last_name":"Calzolari"},{"first_name":"Chu-Ren","full_name":"Huang, Chu-Ren","last_name":"Huang"},{"first_name":"Hansaem","full_name":"Kim, Hansaem","last_name":"Kim"},{"first_name":"James","last_name":"Pustejovsky","full_name":"Pustejovsky, James"},{"full_name":"Wanner, Leo","last_name":"Wanner","first_name":"Leo"},{"full_name":"Choi, Key-Sun","last_name":"Choi","first_name":"Key-Sun"},{"first_name":"Pum-Mo","last_name":"Ryu","full_name":"Ryu, Pum-Mo"},{"first_name":"Hsin-Hsi","full_name":"Chen, Hsin-Hsi","last_name":"Chen"},{"full_name":"Donatelli, Lucia","last_name":"Donatelli","first_name":"Lucia"},{"first_name":"Heng","last_name":"Ji","full_name":"Ji, Heng"},{"last_name":"Kurohashi","full_name":"Kurohashi, Sadao","first_name":"Sadao"},{"first_name":"Patrizia","last_name":"Paggio","full_name":"Paggio, Patrizia"},{"full_name":"Xue, Nianwen","last_name":"Xue","first_name":"Nianwen"},{"full_name":"Kim, Seokhwan","last_name":"Kim","first_name":"Seokhwan"},{"first_name":"Younggyun","last_name":"Hahm","full_name":"Hahm, Younggyun"},{"first_name":"Zhong","last_name":"He","full_name":"He, Zhong"},{"first_name":"Tony Kyungil","full_name":"Lee, Tony Kyungil","last_name":"Lee"},{"full_name":"Santus, Enrico","last_name":"Santus","first_name":"Enrico"},{"first_name":"Francis","last_name":"Bond","full_name":"Bond, Francis"},{"first_name":"Seung-Hoon","last_name":"Na","full_name":"Na, Seung-Hoon"}],"status":"public","type":"conference","publication":"Proceedings of the 29th International Conference on Computational Linguistics","language":[{"iso":"eng"}],"project":[{"name":"TRR 318 - INF: TRR 318 - Project Area INF","_id":"118"}],"_id":"55337","user_id":"3900","department":[{"_id":"600"},{"_id":"660"}],"place":"Gyeongju, Republic of Korea","year":"2022","citation":{"ama":"Wachsmuth H, Alshomary M. “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In: Calzolari N, Huang C-R, Kim H, et al., eds. <i>Proceedings of the 29th International Conference on Computational Linguistics</i>. International Committee on Computational Linguistics; 2022:344–354.","chicago":"Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations.” In <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, edited by Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, et al., 344–354. Gyeongju, Republic of Korea: International Committee on Computational Linguistics, 2022.","ieee":"H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations,” in <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, 2022, pp. 344–354.","apa":"Wachsmuth, H., &#38; Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, &#38; S.-H. Na (Eds.), <i>Proceedings of the 29th International Conference on Computational Linguistics</i> (pp. 344–354). International Committee on Computational Linguistics.","mla":"Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations.” <i>Proceedings of the 29th International Conference on Computational Linguistics</i>, edited by Nicoletta Calzolari et al., International Committee on Computational Linguistics, 2022, pp. 344–354.","bibtex":"@inproceedings{Wachsmuth_Alshomary_2022, place={Gyeongju, Republic of Korea}, title={“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations}, booktitle={Proceedings of the 29th International Conference on Computational Linguistics}, publisher={International Committee on Computational Linguistics}, author={Wachsmuth, Henning and Alshomary, Milad}, editor={Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky, James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and Donatelli, Lucia and Ji, Heng and et al.}, year={2022}, pages={344–354} }","short":"H. Wachsmuth, M. Alshomary, in: N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T.K. Lee, E. Santus, F. Bond, S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 344–354."},"page":"344–354","title":"“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations","publisher":"International Committee on Computational Linguistics","date_updated":"2024-07-26T13:05:45Z","date_created":"2024-07-22T13:05:42Z","author":[{"id":"3900","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","first_name":"Henning"},{"first_name":"Milad","full_name":"Alshomary, Milad","id":"73059","last_name":"Alshomary"}]},{"citation":{"apa":"Sengupta, M., Alshomary, M., &#38; Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. <i>Proceedings of the 2022 Workshop on Figurative Language Processing</i>.","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} }","short":"M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.","mla":"Sengupta, Meghdut, et al. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” <i>Proceedings of the 2022 Workshop on Figurative Language Processing</i>, 2022.","ama":"Sengupta M, Alshomary M, Wachsmuth H. Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. In: <i>Proceedings of the 2022 Workshop on Figurative Language Processing</i>. ; 2022.","ieee":"M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.","chicago":"Sengupta, Meghdut, Milad Alshomary, and Henning Wachsmuth. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” In <i>Proceedings of the 2022 Workshop on Figurative Language Processing</i>, 2022."},"year":"2022","date_created":"2022-11-14T08:49:07Z","author":[{"full_name":"Sengupta, Meghdut","id":"99459","last_name":"Sengupta","first_name":"Meghdut"},{"id":"73059","full_name":"Alshomary, Milad","last_name":"Alshomary","first_name":"Milad"},{"first_name":"Henning","last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900"}],"date_updated":"2024-07-26T13:08:46Z","title":"Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning","publication":"Proceedings of the 2022 Workshop on Figurative Language Processing","type":"conference","status":"public","department":[{"_id":"600"},{"_id":"660"}],"user_id":"3900","_id":"34067","project":[{"name":"TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens","_id":"127"}],"language":[{"iso":"eng"}]},{"title":"Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing","supervisor":[{"id":"58701","full_name":"Kersting, Joschka","last_name":"Kersting","first_name":"Joschka"}],"author":[{"full_name":"Ahmed, Mobeen","last_name":"Ahmed","first_name":"Mobeen"}],"date_created":"2021-12-16T15:13:07Z","date_updated":"2023-05-02T13:25:45Z","citation":{"apa":"Ahmed, M. (2022). <i>Knowledge Base Enhanced &#38; User-centric Dialogue Design for OTF Computing</i>.","short":"M. Ahmed, Knowledge Base Enhanced &#38; User-Centric Dialogue Design for OTF Computing, 2022.","bibtex":"@book{Ahmed_2022, title={Knowledge Base Enhanced &#38; User-centric Dialogue Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }","mla":"Ahmed, Mobeen. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design for OTF Computing</i>. 2022.","chicago":"Ahmed, Mobeen. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design for OTF Computing</i>, 2022.","ieee":"M. Ahmed, <i>Knowledge Base Enhanced &#38; User-centric Dialogue Design for OTF Computing</i>. 2022.","ama":"Ahmed M. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design for OTF Computing</i>.; 2022."},"year":"2022","publication_status":"published","has_accepted_license":"1","language":[{"iso":"eng"}],"file_date_updated":"2023-05-02T13:25:27Z","ddc":["004"],"user_id":"58701","department":[{"_id":"600"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"_id":"29000","file":[{"content_type":"application/pdf","success":1,"relation":"main_file","date_updated":"2023-05-02T13:25:27Z","creator":"jkers","date_created":"2023-05-02T13:25:27Z","file_size":3092211,"access_level":"closed","file_name":"Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf","file_id":"44325"}],"status":"public","abstract":[{"lang":"eng","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."}],"type":"mastersthesis"},{"date_updated":"2023-07-05T07:31:17Z","supervisor":[{"first_name":"Henning","id":"3900","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth"}],"author":[{"full_name":"Palushi, Juela","last_name":"Palushi","first_name":"Juela"}],"date_created":"2023-06-27T12:57:57Z","title":"Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks","year":"2022","citation":{"ieee":"J. Palushi, <i>Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks</i>. 2022.","chicago":"Palushi, Juela. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks</i>, 2022.","ama":"Palushi J. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks</i>.; 2022.","apa":"Palushi, J. (2022). <i>Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks</i>.","short":"J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022.","mla":"Palushi, Juela. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks</i>. 2022.","bibtex":"@book{Palushi_2022, title={Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }"},"_id":"45790","project":[{"_id":"9","name":"SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)","grant_number":"160364472"},{"_id":"1","name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ","grant_number":"160364472"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"}],"department":[{"_id":"600"}],"user_id":"477","language":[{"iso":"eng"}],"type":"bachelorsthesis","status":"public"},{"citation":{"short":"V. Budanurmath, Propaganda Technique Detection Using Connotation Frames, 2022.","bibtex":"@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation Frames}, author={Budanurmath, Vinaykumar}, year={2022} }","mla":"Budanurmath, Vinaykumar. <i>Propaganda Technique Detection Using Connotation Frames</i>. 2022.","apa":"Budanurmath, V. (2022). <i>Propaganda Technique Detection Using Connotation Frames</i>.","ieee":"V. Budanurmath, <i>Propaganda Technique Detection Using Connotation Frames</i>. 2022.","chicago":"Budanurmath, Vinaykumar. <i>Propaganda Technique Detection Using Connotation Frames</i>, 2022.","ama":"Budanurmath V. <i>Propaganda Technique Detection Using Connotation Frames</i>.; 2022."},"year":"2022","title":"Propaganda Technique Detection Using Connotation Frames","author":[{"first_name":"Vinaykumar","full_name":"Budanurmath, Vinaykumar","last_name":"Budanurmath"}],"date_created":"2023-06-27T12:56:04Z","supervisor":[{"first_name":"Henning","last_name":"Wachsmuth","id":"3900","full_name":"Wachsmuth, Henning"}],"date_updated":"2023-07-05T07:33:45Z","status":"public","type":"mastersthesis","language":[{"iso":"eng"}],"user_id":"477","department":[{"_id":"600"}],"project":[{"_id":"9","name":"SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)","grant_number":"160364472"},{"grant_number":"160364472","_id":"1","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"}],"_id":"45789"},{"year":"2022","page":"21 - 31","citation":{"ama":"Alshomary M, Rieskamp J, Wachsmuth H. Generating Contrastive Snippets for Argument Search. In: <i>Proceedings of the 9th International Conference on Computational Models of Argument</i>. ; 2022:21-31. doi:<a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>","chicago":"Alshomary, Milad, Jonas Rieskamp, and Henning Wachsmuth. “Generating Contrastive Snippets for Argument Search.” In <i>Proceedings of the 9th International Conference on Computational Models of Argument</i>, 21–31, 2022. <a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>.","ieee":"M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets for Argument Search,” in <i>Proceedings of the 9th International Conference on Computational Models of Argument</i>, 2022, pp. 21–31, doi: <a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>.","short":"M. Alshomary, J. Rieskamp, H. Wachsmuth, in: Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31.","bibtex":"@inproceedings{Alshomary_Rieskamp_Wachsmuth_2022, title={Generating Contrastive Snippets for Argument Search}, DOI={<a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>}, 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} }","mla":"Alshomary, Milad, et al. “Generating Contrastive Snippets for Argument Search.” <i>Proceedings of the 9th International Conference on Computational Models of Argument</i>, 2022, pp. 21–31, doi:<a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>.","apa":"Alshomary, M., Rieskamp, J., &#38; Wachsmuth, H. (2022). Generating Contrastive Snippets for Argument Search. <i>Proceedings of the 9th International Conference on Computational Models of Argument</i>, 21–31. <a href=\"http://dx.doi.org/10.3233/FAIA220138\">http://dx.doi.org/10.3233/FAIA220138</a>"},"title":"Generating Contrastive Snippets for Argument Search","doi":"http://dx.doi.org/10.3233/FAIA220138","date_updated":"2025-02-20T08:22:16Z","date_created":"2022-06-28T09:03:30Z","author":[{"first_name":"Milad","last_name":"Alshomary","id":"73059","full_name":"Alshomary, Milad"},{"first_name":"Jonas","full_name":"Rieskamp, Jonas","id":"77643","last_name":"Rieskamp"},{"full_name":"Wachsmuth, Henning","id":"3900","last_name":"Wachsmuth","first_name":"Henning"}],"status":"public","publication":"Proceedings of the 9th International Conference on Computational Models of Argument","type":"conference","language":[{"iso":"eng"}],"_id":"32247","project":[{"name":"TRR 318 - INF: TRR 318 - Project Area INF","_id":"118"}],"department":[{"_id":"600"},{"_id":"660"}],"user_id":"3900"},{"year":"2022","page":"8782 - 8797","citation":{"ieee":"M. Alshomary, R. El Baff, T. Gurcke, and H. Wachsmuth, “The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments,” in <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 2022, pp. 8782–8797.","chicago":"Alshomary, Milad, Roxanne El Baff, Timon Gurcke, and Henning Wachsmuth. “The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments.” In <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 8782–97, 2022.","ama":"Alshomary M, El Baff R, Gurcke T, Wachsmuth H. The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. In: <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>. ; 2022:8782-8797.","bibtex":"@inproceedings{Alshomary_El Baff_Gurcke_Wachsmuth_2022, title={The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments}, booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics}, author={Alshomary, Milad and El Baff, Roxanne and Gurcke, Timon and Wachsmuth, Henning}, year={2022}, pages={8782–8797} }","short":"M. Alshomary, R. El Baff, T. Gurcke, H. Wachsmuth, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 8782–8797.","mla":"Alshomary, Milad, et al. “The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments.” <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 2022, pp. 8782–97.","apa":"Alshomary, M., El Baff, R., Gurcke, T., &#38; Wachsmuth, H. (2022). The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics</i>, 8782–8797."},"title":"The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments","date_updated":"2025-02-20T08:22:46Z","author":[{"first_name":"Milad","id":"73059","full_name":"Alshomary, Milad","last_name":"Alshomary"},{"first_name":"Roxanne","last_name":"El Baff","full_name":"El Baff, Roxanne"},{"first_name":"Timon","id":"52174","full_name":"Gurcke, Timon","last_name":"Gurcke"},{"last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900","first_name":"Henning"}],"date_created":"2022-04-06T14:05:45Z","status":"public","publication":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics","type":"conference","language":[{"iso":"eng"}],"_id":"30840","project":[{"name":"TRR 318 - INF: TRR 318 - Project Area INF","_id":"118"}],"department":[{"_id":"600"},{"_id":"660"}],"user_id":"3900"},{"year":"2021","citation":{"ama":"Skitalinskaya G, Klaff J, Wachsmuth H. Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale. In: <i>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics</i>. ; 2021:1718-1729.","chicago":"Skitalinskaya, Gabriella, Jonas Klaff, and Henning Wachsmuth. “Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale.” In <i>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics</i>, 1718–29, 2021.","ieee":"G. Skitalinskaya, J. Klaff, and H. Wachsmuth, “Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale,” in <i>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics</i>, 2021, pp. 1718–1729.","apa":"Skitalinskaya, G., Klaff, J., &#38; Wachsmuth, H. (2021). Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale. In <i>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics</i> (pp. 1718–1729).","mla":"Skitalinskaya, Gabriella, et al. “Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale.” <i>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics</i>, 2021, pp. 1718–29.","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} }","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."},"page":"1718-1729","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/"}],"date_updated":"2022-01-06T06:54:19Z","author":[{"first_name":"Gabriella","full_name":"Skitalinskaya, Gabriella","last_name":"Skitalinskaya"},{"full_name":"Klaff, Jonas","last_name":"Klaff","first_name":"Jonas"},{"first_name":"Henning","id":"3900","full_name":"Wachsmuth, Henning","last_name":"Wachsmuth"}],"date_created":"2020-10-16T12:39:27Z","status":"public","type":"conference","publication":"Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics","language":[{"iso":"eng"}],"_id":"20115","user_id":"82920","department":[{"_id":"600"}]}]