InstituteStaff
Henning Wachsmuth

Henning Wachsmuth

Prof. Dr. rer. nat. Henning Wachsmuth
Address
Appelstraße 9a
30167 Hannover
Building
Room
Prof. Dr. rer. nat. Henning Wachsmuth
Address
Appelstraße 9a
30167 Hannover
Building
Room

Publications

Showing entries 1 - 20 out of 93
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Stahl M, Wachsmuth H. Identifying Feedback Types to Augment Feedback Comment Generation. In Proceedings of the 16th International Natural Language Generation Conference. 2023

Alshomary M, El Baff R, Gurcke T, Wachsmuth H. The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments. In Muresan S, Nakov P, Villavicencio A, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics Volume 1: Long Papers. Association for Computational Linguistics (ACL). 2022. p. 8782 - 8797

doi.org/10.48550/arXiv.2203.14563

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doi.org/10.18653/v1/2022.acl-long.601

Bondarenko A, Fröbe M, Kiesel J, Syed S, Gurcke T, Beloucif M et al. Overview of Touché 2022: Argument Retrieval. CEUR Workshop Proceedings. 2022;3180:2867-2903.

Bondarenko A, Fröbe M, Kiesel J, Syed S, Gurcke T, Beloucif M et al. Overview of Touché 2022: Argument Retrieval: Argument Retrieval: Extended Abstract. In Hagen M, Verberne S, Macdonald C, Seifert C, Balog K, Nørvåg K, Setty V, editors, Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Proceedings. Part 2 ed. Springer Science and Business Media Deutschland GmbH. 2022. p. 339-346. (Lecture Notes in Computer Science).

doi.org/10.1007/978-3-030-99739-7_43

Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument Structures in Learner Essays. In Lapesa G, Schneider J, Jo Y, Saha S, editors, Proceedings of the 9th Workshop on Argument Mining. Association for Computational Linguistics (ACL). 2022. p. 51 - 61

Kiesel J, Alshomary M, Handke N, Cai X, Wachsmuth H, Stein B. Identifying the Human Values behind Arguments. In Muresan S, Nakov P, Villavicencio A, editors, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics Volume 1: Long Papers. Association for Computational Linguistics (ACL). 2022. p. 4459 - 4471

doi.org/10.18653/v1/2022.acl-long.306

Lauscher A, Wachsmuth H, Gurevych I, Glavaš G. On the Role of Knowledge in Computational Argumentation. 2022.

doi.org/10.48550/arXiv.2107.00281

Lauscher A, Wachsmuth H, Gurevych I, Glavaš G. Scientia Potentia Est—On the Role of Knowledge in Computational Argumentation. Transactions of the Association for Computational Linguistics. 2022 Dec 22;10(10):1392-1422.

doi.org/10.1162/tacl_a_00525

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

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

Stahl M, Spliethöver M, Wachsmuth H. To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation. In Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science. Abu Dhabi, United Arab Emirates: Association for Computational Linguistics (ACL). 2022

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 Proceedings of the 29th International Conference on Computational Linguistics. Gyeongju: International Committee on Computational Linguistics. 2022. p. 344 - 354

doi.org/10.48550/arXiv.2209.02508

Ajjour Y, Al-Khatib K, Cimiano P, El Baff R, Ell B, Stein B et al. Preface. CEUR Workshop Proceedings. 2021;2921.

Al-Khatib K, Trautner L, Wachsmuth H, Hou Y, Stein B. Employing argumentation knowledge graphs for neural argument generation. In ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL). 2021. p. 4744-4754

Alshomary M, Chen WF, Gurcke T, Wachsmuth H. Belief-based Generation of Argumentative Claims. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics (ACL). 2021. p. 224-233

doi.org/10.48550/arXiv.2101.09765

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doi.org/10.18653/v1/2021.eacl-main.17

Alshomary M, Syed S, Dhar A, Potthast M, Wachsmuth H. Counter-Argument Generation by Attacking Weak Premises: Counter-Argument Generation by Attacking Weak Premises. In Zong C, Xia F, Li W, Navigli R, editors, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics (ACL). 2021. p. 1816-1827

doi.org/10.18653/v1/2021.findings-acl.159

Alshomary M, Gurke T, Syed S, Heinisch P, Spliethöver M, Cimiano P et al. Key Point Analysis via Contrastive Learning and Extractive Argument Summarization. In Proceedings of The 8th Workshop on Argument Mining,. Association for Computational Linguistics (ACL). 2021. p. 184-189

Alshomary M, Wachsmuth H. Toward audience-aware argument generation. Patterns. 2021 Jun;2(6). 100253.

doi.org/10.1016/j.patter.2021.100253

Barrow J, Jain R, Lipka N, Dernoncourt F, Morariu VI, Manjunatha V et al. Syntopical graphs for computational argumentation tasks. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing. Association for Computational Linguistics (ACL). 2021. p. 1583-1595

doi.org/10.18653/v1/2021.acl-long.126

Bondarenko A, Gienapp L, Fröbe M, Beloucif M, Ajjour Y, Panchenko A et al. Overview of Touché 2021: Argument Retrieval: Extended Abstract. In Hiemstra D, Moens M-F, Mothe J, Perego R, Potthast M, Sebastiani F, editors, Advances in Information Retrieval: 43rd European Conference on IR Research, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 574-582. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

doi.org/10.1007/978-3-030-72240-1_67