MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Tracking
MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Tracking
Dialogue state tracking (DST) aims to convert the dialogue history into dialogue states which consist of slot-value pairs. As condensed structural information memorizes all history information, the dialogue state in the previous turn is typically adopted as the input for predicting the current state by DST models. However, these models …