6 relies on g θ being able to explore other candidates during sampling.
this negative sampling by corruption approach is also used in learning knowledge graph embeddings (Bordes et al., 2013;Lin et al., 2015;Ji et al., 2015;Wang et al., 2014;trouillon et al., 2016;Yang et al., 2014;Dettmers et al., 2017), order embeddings (Vendrov et al., 2016), caption generation (Dai and Lin, 2017), etc.