Abstract
Argument generation is a challenging task whose research is timely considering its potential impact on social media and the dissemination of information. Here we suggest a pipeline based on GPT-2 for generating coherent claims, and explore the types of claims that it produces, and their veracity, using an array of manual and automatic assessments. In addition, we explore the interplay between this task and the task of Claim Retrieval, showing how they can complement one another.- Anthology ID:
- 2020.findings-emnlp.47
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 528–544
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.47
- DOI:
- 10.18653/v1/2020.findings-emnlp.47
- Cite (ACL):
- Shai Gretz, Yonatan Bilu, Edo Cohen-Karlik, and Noam Slonim. 2020. The workweek is the best time to start a family – A Study of GPT-2 Based Claim Generation. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 528–544, Online. Association for Computational Linguistics.
- Cite (Informal):
- The workweek is the best time to start a family – A Study of GPT-2 Based Claim Generation (Gretz et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2020.findings-emnlp.47.pdf