Recently, <cite>Zhong et al. (2018)</cite> proposed a model based on training a binary classifier for each slot-value, Global-Locally Self Attentive encoder (GLAD, by employing recurrent and self attention for each utterance and previous system actions, and measuring similaity of these computed representation to each slot-value, which achieve state of the art results on WoZ and DSTC2 (Williams et al., 2013) datasets.