Argument Novelty and Validity Assessment via Multitask and Transfer Learning
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.
Details
- Organisation(s)
-
Institute of Artificial Intelligence
Natural Language Processing Section
- Type
- Conference contribution
- Volume
- 29
- Pages
- 111-114
- No. of pages
- 4
- Publication date
- 2022
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Computational Theory and Mathematics, Computer Science Applications, Theoretical Computer Science
- Sustainable Development Goals
- SDG 4 - Quality Education
- Electronic version(s)
-
https://aclanthology.org/2022.argmining-1.10.pdf (Access:
Open
)
Cite
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