Papers by Maximilian Heinrich
Few-Shot Learning for Argument Aspects of the Nuclear Energy Debate (2022.lrec-1)
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| Challenge: | Existing methods to classify aspects of arguments are expensive and require training data for further aspects and topics. |
| Approach: | They propose a supervised aspect-based argument mining task to classify arguments into semantically coherent groups referring to the same defined aspect categories. |
| Outcome: | The proposed method is able to predict share of arguments in a British newspaper corpus with 50 to 100 examples per aspect. |
The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments (2024.lrec-main)
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Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary, Maximilian Heinrich, Nicolas Handke, Xiaoni Cai, Valentin Barriere, Doratossadat Dastgheib, Omid Ghahroodi, MohammadAli SadraeiJavaheri, Ehsaneddin Asgari, Lea Kawaletz, Henning Wachsmuth, Benno Stein
| Challenge: | Cultural norms can influence the prioritization of values, leading to distinct perspectives on debatable topics. |
| Approach: | They present a Touché23-ValueEval dataset that annotates 4780 new arguments and annotated 54 human values. |
| Outcome: | The Touché23-ValueEval dataset doubles the original Webis-ArgValués-22 dataset to 9324 arguments. |