Multi-domain Dialogue State Tracking

29 papers with code • 6 benchmarks • 2 datasets

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Use these libraries to find Multi-domain Dialogue State Tracking models and implementations

Most implemented papers

MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines

budzianowski/multiwoz LREC 2020

To fix the noisy state annotations, we use crowdsourced workers to re-annotate state and utterances based on the original utterances in the dataset.

SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking


In goal-oriented dialog systems, belief trackers estimate the probability distribution of slot-values at every dialog turn.

Efficient Dialogue State Tracking by Selectively Overwriting Memory

clovaai/som-dst ACL 2020

This mechanism consists of two steps: (1) predicting state operation on each of the memory slots, and (2) overwriting the memory with new values, of which only a few are generated according to the predicted state operations.

Global-Locally Self-Attentive Dialogue State Tracker

salesforce/glad 19 May 2018

Dialogue state tracking, which estimates user goals and requests given the dialogue context, is an essential part of task-oriented dialogue systems.

Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing

jojonki/MultiWOZ-Parser ACL 2018

Robust dialogue belief tracking is a key component in maintaining good quality dialogue systems.

Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems

jasonwu0731/trade-dst ACL 2019

Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking.

Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering

alexa/dstqa 7 Nov 2019

Multi-domain dialogue state tracking (DST) is a critical component for conversational AI systems.

CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers

salesforce/coco-dst ICLR 2021

Dialogue state trackers have made significant progress on benchmark datasets, but their generalization capability to novel and realistic scenarios beyond the held-out conversations is less understood.

Jointly Optimizing State Operation Prediction and Value Generation for Dialogue State Tracking

zengyan-97/Transformer-DST 24 Oct 2020

However, in such a stacked encoder-decoder structure, the operation prediction objective only affects the BERT encoder and the value generation objective mainly affects the RNN decoder.

Know Thy Strengths: Comprehensive Dialogue State Tracking Diagnostics

budzianowski/multiwoz 15 Dec 2021

Recent works that revealed the vulnerability of dialogue state tracking (DST) models to distributional shifts have made holistic comparisons on robustness and qualitative analyses increasingly important for understanding their relative performance.