Previous works have shown that scientific papers specific pre-trained word embeddings can improve training for scientific RC models (Rotsztejn et al., 2018;Hettinger et al., 2018;Jin et al., 2018;Luan et al., 2018).
in this work, we trained the scientific papers specific word embeddings on the ACL Anthology Reference Corpus (Bird et al., 2008) by the skip-gram NN architecture made available by the Gensim word2vec tool.