Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation
Table 7: BLEU scores (average results on the 5 test sets) of the two encoders vs. the single shared encoder for the pre-training model on the 900K-sentence corpus.
['[BOLD] Methods', '[BOLD] BLEU']
We conducted experiments to compare the two encoders vs. the single shared encoder for the pre-training model. Obviously, the two-encoder network is better than the single shared encoder. This indicates that the two separate encoders are better at capturing the discourse dependencies between the previous and the current sentence and between the next and the current sentence than the single encoder. We conjecture that this is because the dependencies on the previous sentence are different from those on the next sentence.