BP-Transformer: Modelling Long-Range Context via Binary Partitioning
Table 1: Test accuracy on SST-5 and IMDB. In BPT, k=2 and k=4 for SST and IMDB respectively. The last model used word embeddings pretrained with translation and additional character-level embeddings.
['Model', 'SST-5', 'IMDB']
On SST-5, our model outperforms Transformer and LSTM based models. On IMDB, our proposed model outperforms a bidirectional LSTM initialized with pre-trained character embedding and CoVe embedding mccann2017learned.