For RAWFC, we constructed it from scratch by collecting the claims from Snopes and relevant raw reports by retrieving claim keywords. To alleviate the dependency of fact-checked reports, RAWFC was constructed by using raw reports (from scratch), where gold labels refer to Snopes. Each instance in the train/val/test set is presented as a signle file.
Provide:
Variants: LIAR
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Fake News Detection | HiSS | Towards LLM-based Fact Verification on … | 2023-09-30 |
Fake News Detection | ReAct | Towards LLM-based Fact Verification on … | 2023-09-30 |
Fake News Detection | Standard prompting with articles | Towards LLM-based Fact Verification on … | 2023-09-30 |
Fake News Detection | CoT | Towards LLM-based Fact Verification on … | 2023-09-30 |
Fake News Detection | Persuasive Writing Strategy | Using Persuasive Writing Strategies to … | 2022-11-11 |
Fake News Detection | CofCED | A Coarse-to-fine Cascaded Evidence-Distillation Neural … | 2022-09-29 |
Recent papers with results on this dataset: