Coreferential Reasoning Learningfor Language Representation
Table 4: Results on FEVER test set measured by label accuracy (LA) and FEVER. The FEVER score evaluates the model performance and considers whether the golden evidence is provided. Results with ∗, +, # are from Zhou et al. (2019), Nie et al. (2019) and Liu et al. (2019b) respectively.
['Model', 'LA', 'FEVER']
KGAT with CorefBERTBase outperforms KGAT with BERTBase by 0.4% FEVER score. KGAT with CorefRoBERTaLarge gains 1.4% FEVER score improvement compared to the model with RoBERTaLarge, which makes our model perform the best compared with all previously published research. It again demonstrates the effectiveness of our model. The CorefBERT, which incorporates coreference information in distant-supervised pre-training, helps to verify if the claim and evidence discuss about the same mentions, such as person or object.