Frustratingly Poor Performance of Reading Comprehension Models on Non-adversarial Examples
Table 2: Results of the 5 models when trained on original RACE and tested on a subset of RACE test set (500 examples) and on the corresponding P5 created using this test set
['Dataset', 'Models GAR', 'Models SAR', 'Models DCN', 'Models BiDAF', 'Models MNR']
We also evaluate models on the human annotated datasets i.e., P5, where annotators select only the sentences required to answer the query and O3(H), where the most confusing option indicated by annotators is dropped.