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Table 4: Effect (in Acc) of using the training mechanisms Joint Training (JT), Prediction Regularization (PR), and Stepwise Pretraining (SP) in LeTraNets.
['[EMPTY]', 'Mov_en', 'Res_en', 'Res_en', 'Mov_ko', 'Mov_ko']
We investigate the performance of LeTraNets when the training mechanisms are not used. Specifically, we perform ablation tests on the Joint Training (JT), Prediction Regularization (PR), and Stepwise Pretraining (SP) mechanisms. Also, when used individually, all the training mechanisms boost up the performance of the model. Hence, we confirm that the training mechanisms help LeTraNets achieve good performance on the task.