Is there any advantage of using BERT over Snips-NLU for slot-filling?

Slot Filling on ATIS ; 1 CTRAN ; 2 Bi-model with a decoder ; 3 Joint BERT ; 4 JointBERT-CAE

This is a pretrained Bert based model with 2 linear classifier heads on the top of it, one for classifying an intent of the query and another for classifying

bert for joint intent classification and slot filling Predict intent and slot at the same time from one BERT model ; total_loss = intent_loss + coef * slot_loss (Change coef with --slot_loss_coef

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