Moreover, unlike the prior work that required discrete token generation to interpret the pretrained word embeddings (Noraset et al., 2017;Gadetsky et al., 2018;, we reformulate the definition modeling task from an NLG problem to a classification problem via learning a mapping between two semantically continuous spaces, which greatly simplifies the hardness, making significant improvement as shown in Table 2.
as the input representations of Noraset et al.