Multi-domain Dialogue State Tracking
29 papers with code • 6 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Multi-domain Dialogue State Tracking
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Libraries
Use these libraries to find Multi-domain Dialogue State Tracking models and implementations
MultiWOZ
SGD
Most implemented papers
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
budzianowski/multiwoz
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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
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
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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
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
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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
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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
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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
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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
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.
