---
_id: '34051'
abstract:
- lang: eng
  text: 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.
author:
- first_name: Milad
  full_name: Alshomary, Milad
  id: '73059'
  last_name: Alshomary
- first_name: Maja
  full_name: Stahl, Maja
  id: '77647'
  last_name: Stahl
citation:
  ama: 'Alshomary M, Stahl M. Argument Novelty and Validity Assessment via Multitask
    and Transfer Learning. In: <i>Proceedings of the 9th Workshop on Argument Mining</i>.
    International Conference on Computational Linguistics; 2022:111–114.'
  apa: Alshomary, M., &#38; Stahl, M. (2022). Argument Novelty and Validity Assessment
    via Multitask and Transfer Learning. <i>Proceedings of the 9th Workshop on Argument
    Mining</i>, 111–114.
  bibtex: '@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} }'
  chicago: 'Alshomary, Milad, and Maja Stahl. “Argument Novelty and Validity Assessment
    via Multitask and Transfer Learning.” In <i>Proceedings of the 9th Workshop on
    Argument Mining</i>, 111–114. Online and in Gyeongju, Republic of Korea: International
    Conference on Computational Linguistics, 2022.'
  ieee: M. Alshomary and M. Stahl, “Argument Novelty and Validity Assessment via Multitask
    and Transfer Learning,” in <i>Proceedings of the 9th Workshop on Argument Mining</i>,
    2022, pp. 111–114.
  mla: Alshomary, Milad, and Maja Stahl. “Argument Novelty and Validity Assessment
    via Multitask and Transfer Learning.” <i>Proceedings of the 9th Workshop on Argument
    Mining</i>, International Conference on Computational Linguistics, 2022, pp. 111–114.
  short: '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.'
date_created: 2022-11-10T09:51:45Z
date_updated: 2022-11-15T08:49:10Z
language:
- iso: eng
page: 111–114
place: Online and in Gyeongju, Republic of Korea
publication: Proceedings of the 9th Workshop on Argument Mining
publication_status: published
publisher: International Conference on Computational Linguistics
status: public
title: Argument Novelty and Validity Assessment via Multitask and Transfer Learning
type: conference
user_id: '77647'
year: '2022'
...