OpenFC: Learning Verification Policies towards Open-Search Fact Checking
Open-search fact checking is not merely retrieval followed by classification, but a sequential decision problem in which every query, source visit, and stopping decision reshapes the evidence available for verification. Yet existing systems often distribute these decisions across predefined pipelines or separately prompted modules rather than learning them as a unified task-specific policy. We introduce \textbf{OpenFC}, a unified verification-policy training framework that post-trains Qwen3-8B as a compact next-action controller over reasoning, evidence acquisition, and stopping. OpenFC learns this policy in two stages. \textbf{Stepwise-Calibrated Cold Start (SCCS)} uses a strong training...
| Authors | Xinming Wang, Kaixiang Qiu, Yansong Lin et al. |
|---|---|
| Primary category | cs.AI |
| Published | 27 September 2026 |
| Last updated at source | 27 September 2026 |
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