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Contrastive embedding trained unsupervisedly
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Model is trained based on contrastive loss and 'Fake news classification' as validation task.
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MLP is used as external classifier for validation task given the resulting embedding from trained model.
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Contrastive embedding trained unsupervisedly to implicitly contradict factual evidences and claims . The dataset is based on online public report for fake news detection.
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Model is trained based on contrastive loss and 'Fake news classification' as validation task.
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MLP is used as external classifier for validation task given the resulting embedding from trained model.
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