Hierarchical Graph Network for Multi-hop Question Answering
Table 1: Results on the test set of HotpotQA in the Distractor setting. HGN achieves state-of-the-art results at the time of submission (Dec. 1, 2019). (†) indicates unpublished work. RoBERTa-large is used for context encoding.
['Model', 'Ans EM', 'Ans F1', 'Sup EM', 'Sup F1', 'Joint EM', 'Joint F1']
Table 1 and Table 2 summarize our results on the hidden test set of HotpotQA in the Distractor and Fullwiki setting, respectively. The proposed HGN outperforms both published and unpublished work on every metric by a significant margin. For example, HGN achieves a Joint EM/F1 score of 43.57/71.03 and 35.63/59.86 on the Distractor and Fullwiki setting, respectively, with an absolute improvement of 2.36/0.38 and 6.45/4.55 points over the previous state of the art.