RTM Ensemble Learning Results at Quality Estimation Task

Ergun Biçici. RTM Ensemble Learning Results at Quality Estimation Task. In Proc. of the Fifth Conference on Statistical Machine Translation (WMT20), Online, November 2020.

We obtain new results using referential translation machines (RTMs) with predictions mixed and stacked to obtain a better mixture of experts prediction. We are able to achieve better results than the baseline model in Task 1 subtasks. Our stacking results significantly improve the results on the training sets but decrease the test set results. RTMs can achieve to become the 5th among 13 models in ru-en subtask and 5th in the multilingual track of sentence-level Task 1 based on MAE.