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Found 6 papers, 3 papers with code
Schema Graph-Guided Prompt for Multi-Domain Dialogue State Tracking
Tracking dialogue states is an essential topic in task-oriented dialogue systems, which involve filling in the necessary information in pre-defined slots corresponding to a schema.
Choice Fusion as Knowledge for Zero-Shot Dialogue State Tracking
With the demanding need for deploying dialogue systems in new domains with less cost, zero-shot dialogue state tracking (DST), which tracks user's requirements in task-oriented dialogues without training on desired domains, draws attention increasingly.
Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State Tracking
As an essential component in task-oriented dialogue systems, dialogue state tracking (DST) aims to track human-machine interactions and generate state representations for managing the dialogue.
Knowledge Augmented BERT Mutual Network in Multi-turn Spoken Dialogues
Modern spoken language understanding (SLU) systems rely on sophisticated semantic notions revealed in single utterances to detect intents and slots.
A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act Detection
The success of interactive dialog systems is usually associated with the quality of the spoken language understanding (SLU) task, which mainly identifies the corresponding dialog acts and slot values in each turn.
Deep Learning Enabled Semantic Communication Systems
To justify the performance of semantic communications accurately, we also initialize a new metric, named sentence similarity.
