LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification

@inproceedings{Chen2020LORENLR,
  title={LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification},
  author={Jiangjie Chen and Qiaoben Bao and Changzhi Sun and Xinbo Zhang and Jiaze Chen and Hao Zhou and Yanghua Xiao and Lei Li},
  booktitle={AAAI Conference on Artificial Intelligence},
  year={2020}
}
Given a natural language statement, how to verify its veracity against a large-scale textual knowledge source like Wikipedia? Most existing neural models make predictions without giving clues about which part of a false claim goes wrong. In this paper, we propose LOREN, an approach for interpretable fact verification. We decompose the verification of the whole claim at phrase-level, where the veracity of the phrases serves as explanations and can be aggregated into the final verdict according… 

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