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DTCA: Decision Tree-based Co-Attention Networks for Explainable Claim Verification
Simultaneously, the discovered evidence only roughly aims at the interpretability of the whole sequence of claims but insufficient to focus on the false parts of claims.
Discovering Differential Features: Adversarial Learning for Information Credibility Evaluation
A series of deep learning approaches extract a large number of credibility features to detect fake news on the Internet.
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection
Recently, neural networks based on multi-task learning have achieved promising performance on fake news detection, which focus on learning shared features among tasks as complementary features to serve different tasks.
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