✨REFLEX: Self-Refining Explainable Fact-Checking via Disentangling Truth into Style and Substance

📝 Summary:
REFLEX is a new fact-checking method that uses internal model knowledge to improve verdict accuracy and explanation quality. It disentangles truth into style and substance via adaptive activation signals, achieving state-of-the-art performance with minimal training data. This approach also shows ...

🔹 Publication Date: Published on Nov 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.20233
• PDF: https://arxiv.org/pdf/2511.20233

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#FactChecking #ExplainableAI #MachineLearning #AI #NLP

✨Towards Comprehensive Stage-wise Benchmarking of Large Language Models in Fact-Checking

📝 Summary:
FactArena is a new automated framework for comprehensively benchmarking LLMs across the entire fact-checking pipeline, including claim extraction and evidence retrieval. It reveals significant gaps between claim verification accuracy and overall fact-checking competence, highlighting the need for...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02669
• PDF: https://arxiv.org/pdf/2601.02669

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✓ https://t.me/DataScienceT

#LLM #FactChecking #AI #NLP #Benchmarking