Papers by Sunna Torge
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. |