Argument Novelty and Validity Assessment via Multitask and Transfer Learning

authored by

Milad Alshomary, Maja Stahl

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.

Organisation(s)

Institute of Artificial Intelligence
Natural Language Processing Section

Type

Conference contribution

Pages

111-114

Publication date

2022

Publication status

Published

Peer reviewed

Yes

Sustainable Development Goals

SDG 4 - Quality Education

Electronic version(s)

https://aclanthology.org/2022.argmining-1.10.pdf (Access: Open)