Towards Decoding as Continuous Optimisation in Neural Machine Translation
Table 3: The BLEU evaluation results across evaluation datasets for EG algorithm variants against the baselines; bold: statistically significantly better than the best greedy or beam baseline, †: best performance on dataset.
['[EMPTY]', 'BTEC', 'TEDTalks', 'WMT']
For the EG algorithm with greedy initialisation (top), we see small but consistent improvements in terms of BLEU. Beam initialisation led to overall higher BLEU scores, and again demonstrating a similar pattern of improvements, albeit of a lower magnitude, over the initialisation values.