1. Ergun Biçici. RTM Ensemble Learning Results at Quality Estimation Task. In Proc. of the Fifth Conf. on Machine Translation (WMT20), Online, 11 2020. [WWW] Keyword(s): Machine Translation, Machine Learning, Performance Prediction. Abstract:

   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 $5$th among $13$ models in ru-en subtask and $5$th in the multilingual track of sentence-level Task 1 based on MAE.

   
   

   @InProceedings{Bicici:RTM:WMT2020,
   author = {Ergun Bi\c{c}ici},
   title = {{RTM} Ensemble Learning Results at Quality Estimation Task},
   booktitle = {Proc. of the {F}ifth {C}onf. on {M}achine {T}ranslation ({WMT20})},
   month = {11},
   year = {2020},
   address = {Online},
   keywords = {Machine Translation, Machine Learning, Performance Prediction},
   abstract = {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 $5$th among $13$ models in ru-en subtask and $5$th in the multilingual track of sentence-level Task 1 based on MAE.},
   url = {https://aclanthology.org/2020.wmt-1.114},
   
   }
   

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