Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual Claims
This paper presents the latest developments to ClaimBuster?s claim-spotting model, which tackles the critical task of identifying check-worthy claims from large streams of information. We introduce the first adversarially-regularized, transformer-based claim-spotting model, which achieves state-of-t...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
ACM
2024
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| Online Access: | https://hdl.handle.net/1721.1/156666 |