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PANACEA: An Automated Misinformation Detection System on COVID-19

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arxiv 2303.01241 v1 pith:Y6OLEHM2 submitted 2023-02-28 cs.CL cs.LG

classification cs.CLcs.LG
keywords detectionpanaceaableautomatedbasecovid-19fact-checkingknowledge
verification ladder T0 review T1 audit T2 compute T3 formal
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In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-of-the-art approaches. It is also able to give automated veracity assessment and ranked supporting evidence with the stance towards the claim to be checked. In addition, PANACEA adapts the bi-directional graph convolutional networks model, which is able to detect rumours based on comment networks of related tweets, instead of relying on the knowledge base. This rumour detection module assists by warning the users in the early stages when a knowledge base may not be available.

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    A three-stage RAG pipeline generates a cited summary (GenText) from PubMed Central passages and ranks health documents by topical relevance plus alignment with that summary, outperforming baselines on CLEF eHealth and...

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