ClaimCheck: Real-Time Fact-Checking with Small Language Models

• URL: http://arxiv.org/abs/2510.01226v1
• Date: Mon, 22 Sep 2025 21:18:08 GMT
• Title: ClaimCheck: Real-Time Fact-Checking with Small Language Models
• Authors: Akshith Reddy Putta, Jacob Devasier, Chengkai Li,
• Abstract summary: ClaimCheck is an LLM-guided automatic fact-checking system designed to verify real-world claims.<n>Unlike prior systems that rely on large, closed-source models, ClaimCheck employs a transparent, stepwise verification pipeline.<n>Each module is optimized for small LLMs, allowing the system to deliver accurate and interpretable fact-checking.
• Score: 5.305110876082343
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce ClaimCheck, an LLM-guided automatic fact-checking system designed to verify real-world claims using live Web evidence and small language models. Unlike prior systems that rely on large, closed-source models and static knowledge stores, ClaimCheck employs a transparent, stepwise verification pipeline that mirrors human fact-checking workflows consisting of Web search query planning, Web-based evidence retrieval and summarization, evidence synthesis and re-retrieval, and claim verdict evaluation. Each module is optimized for small LLMs, allowing the system to deliver accurate and interpretable fact-checking with significantly lower computational requirements. Despite using a much smaller Qwen3-4B model, ClaimCheck achieves state-of-the-art accuracy of 76.4% on the AVeriTeC dataset, outperforming previous approaches using LLaMA3.1 70B and GPT-4o. Extensive ablations demonstrate that careful modular design and prompting strategies can overcome the limitations of smaller LLMs. To promote accessibility and transparency, we provide a public demo at https://idir.uta.edu/claimcheck.

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