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# Code for Paper Knowing What You Know: Calibrating Dialogue Belief StateDistributions via Ensembles
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Implementation of different uncertainty in Deep Learning methods for improved Dialogue ***Belief*** Tracking.
## NBT Model
Slot Utterance Matching Belief Tracker transformer. Using BERT language model fine tuning, a slot utterance matching Attention mechanism and a RNN latent state tracker to generate a latent belief state. Further embedding distance comparison is used for generating model logits.
## Uncertainty
### Loss
* Standard Cross Entropy Loss
* Label Smoothing KL divergence Loss (improved uncertainty)
* Belief Matching (Dirichlet activation function with ELBO Loss)