Previous studies (Shang et al., 2018;Tao et al., 2018;Mou et al., 2016) formulated the training of matching models as binary classification learning, where negative sampling is used to free human annotation.
for query q and golden response r + , a negative response r − can be randomly sampled from other responses in the training set.