Detecting Credible, Unreliable, and Leaked Evidence for Robust Automated Fact-Checking

Automated fact-checking systems often rely on external evidence from the web, but this evidence can be unreliable or leaked from existing fact-checking articles, undermining the effectiveness of such systems. This work proposes a comprehensive approach to evidence verification and filtering to address these challenges.