Time-aware Large Kernel Convolutions
Table 2: Machine translation accuracy in terms of BLEU for WMT En-De and WMT En-Fr on newstest2014.
['Model', 'Param (En-De)', 'WMT En-De', 'WMT En-Fr']
We demonstrate the effectiveness of our model in the WMT En-De and WMT En-Fr translation benchmarks. Specifically, our method was able to match the state-of-the-art score on WMT En-Fr, a benchmark dataset that is considered indicative for the effectiveness of a method due to the large number of training examples (36M) it contains. Additionally for WMT En-De, our method is only 0.1 BLEU points behind the current state-of-the-art score. It is important to underline, however, that our method uses the least number of parameters compared to the other counterpart methods.