This includes datasets that test a system's ability to extract factual answers from text (Rajpurkar et al., 2016;Nguyen et al., 2016;Trischler et al., 2016;Mostafazadeh et al., 2016;Su et al., 2016), as well as datasets that emphasize commonsense inference, such as entailment between sentences (Bowman et al., 2015;Williams et al., 2018).
there are growing concerns regarding the ability of NLU systems-and neural networks more generally-to generalize in a systematic and robust way (Bahdanau et al., 2019;Lake and Baroni, 2018;Johnson et al., 2017).