Multi-domain Dialogue State Tracking
29 papers with code • 6 benchmarks • 2 datasets
Libraries
Use these libraries to find Multi-domain Dialogue State Tracking models and implementationsMost implemented papers
A Sequence-to-Sequence Approach to Dialogue State Tracking
This paper is concerned with dialogue state tracking (DST) in a task-oriented dialogue system.
Knowledge-Aware Graph-Enhanced GPT-2 for Dialogue State Tracking
Dialogue State Tracking is central to multi-domain task-oriented dialogue systems, responsible for extracting information from user utterances.
Effective Sequence-to-Sequence Dialogue State Tracking
We also explore using Pegasus, a span prediction-based pre-training objective for text summarization, for the state tracking model.
Dialogue State Tracking with a Language Model using Schema-Driven Prompting
Task-oriented conversational systems often use dialogue state tracking to represent the user's intentions, which involves filling in values of pre-defined slots.
"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversations
Most prior work in dialogue modeling has been on written conversations mostly because of existing data sets.
Robustness through Data Augmentation Loss Consistency
Our experiments show that DAIR consistently outperforms ERM and DA-ERM with little marginal computational cost and sets new state-of-the-art results in several benchmarks involving covariant data augmentation.
Amendable Generation for Dialogue State Tracking
In this paper, we propose a novel Amendable Generation for Dialogue State Tracking (AG-DST), which contains a two-pass generation process: (1) generating a primitive dialogue state based on the dialogue of the current turn and the previous dialogue state, and (2) amending the primitive dialogue state from the first pass.
Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State Tracking
In this paper, we hypothesize that dialogue summaries are essentially unstructured dialogue states; hence, we propose to reformulate dialogue state tracking as a dialogue summarization problem.
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.