Large Language Models Require Curated Context for Reliable Political Fact-Checking—Even with Reasoning and Web Search (2026.findings-acl)
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| Challenge: | Large language models (LLMs) have raised hopes for automated end-to-end fact-checking, but prior studies report mixed results. |
| Approach: | They evaluate 15 large language models on 6,000 claims fact-checked by PolitiFact . standard models perform poorly, reasoning offers minimal benefits, and web search provides only moderate gains . |
| Outcome: | The models predict claim veracity and a curated RAG system improved macro F1 by 233% on average across model variants. |
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