Argument Novelty and Validity Assessment via Multitask and Transfer Learning
M. Alshomary, M. Stahl, in: Proceedings of the 9th Workshop on Argument Mining, International Conference on Computational Linguistics, Online and in Gyeongju, Republic of Korea, 2022, pp. 111–114.
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Abstract
An argument is a constellation of premises reasoning towards a certain conclusion. The automatic generation of conclusions is becoming a very prominent task, raising the need for automatic measures to assess the quality of these generated conclusions. The SharedTask at the 9th Workshop on Argument Mining proposes a new task to assess the novelty and validity of a conclusion given a set of premises. In this paper, we present a multitask learning approach that transfers the knowledge learned from the natural language inference task to the tasks at hand. Evaluation results indicate the importance of both knowledge transfer and joint learning, placing our approach in the fifth place with strong results compared to baselines.
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Proceedings of the 9th Workshop on Argument Mining
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111–114
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Alshomary M, Stahl M. Argument Novelty and Validity Assessment via Multitask and Transfer Learning. In: Proceedings of the 9th Workshop on Argument Mining. International Conference on Computational Linguistics; 2022:111–114.
Alshomary, M., & Stahl, M. (2022). Argument Novelty and Validity Assessment via Multitask and Transfer Learning. Proceedings of the 9th Workshop on Argument Mining, 111–114.
@inproceedings{Alshomary_Stahl_2022, place={Online and in Gyeongju, Republic of Korea}, title={Argument Novelty and Validity Assessment via Multitask and Transfer Learning}, booktitle={Proceedings of the 9th Workshop on Argument Mining}, publisher={International Conference on Computational Linguistics}, author={Alshomary, Milad and Stahl, Maja}, year={2022}, pages={111–114} }
Alshomary, Milad, and Maja Stahl. “Argument Novelty and Validity Assessment via Multitask and Transfer Learning.” In Proceedings of the 9th Workshop on Argument Mining, 111–114. Online and in Gyeongju, Republic of Korea: International Conference on Computational Linguistics, 2022.
M. Alshomary and M. Stahl, “Argument Novelty and Validity Assessment via Multitask and Transfer Learning,” in Proceedings of the 9th Workshop on Argument Mining, 2022, pp. 111–114.
Alshomary, Milad, and Maja Stahl. “Argument Novelty and Validity Assessment via Multitask and Transfer Learning.” Proceedings of the 9th Workshop on Argument Mining, International Conference on Computational Linguistics, 2022, pp. 111–114.
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