Dialogue State Tracking Edit Task
Natural Language Processing • Dialogue
About
Dialogue state tacking consists of determining at each turn of a dialogue the full representation of what the user wants at that point in the dialogue, which contains a goal constraint, a set of requested slots, and the user's dialogue act.
Benchmarks
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Greatest papers with code
CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
TACL 2020
• fighting41love/funNLP
• 
To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.
A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset
• NVIDIA/NeMo
•
Dialog State Tracking (DST) is one of the most crucial modules for goal-oriented dialogue systems.
DATA AUGMENTATION DIALOGUE STATE TRACKING GOAL-ORIENTED DIALOGUE SYSTEMS
MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems
EMNLP 2020
• budzianowski/multiwoz
•
In this paper, we propose Minimalist Transfer Learning (MinTL) to simplify the system design process of task-oriented dialogue systems and alleviate the over-dependency on annotated data.
DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING
MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselines
WS 2020
• budzianowski/multiwoz
•
We also benchmark a few state of the art dialogue state tracking models on the corrected dataset to facilitate comparison for future work.
A Simple Language Model for Task-Oriented Dialogue
NeurIPS 2020
• budzianowski/multiwoz
•
Task-oriented dialogue is often decomposed into three tasks: understanding user input, deciding actions, and generating a response.
DIALOGUE STATE TRACKING LANGUAGE MODELLING TRANSFER LEARNING
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
LREC 2020
• budzianowski/multiwoz
•
To fix the noisy state annotations, we use crowdsourced workers to re-annotate state and utterances based on the original utterances in the dataset.
Ranked #6 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.1
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
ACL 2019
• jasonwu0731/trade-dst
•
Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking.
Ranked #6 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING
Schema-Guided Dialogue State Tracking Task at DSTC8
The goal of this task is to develop dialogue state tracking models suitable for large-scale virtual assistants, with a focus on data-efficient joint modeling across domains and zero-shot generalization to new APIs.
Global-Locally Self-Attentive Dialogue State Tracker
Dialogue state tracking, which estimates user goals and requests given the dialogue context, is an essential part of task-oriented dialogue systems.
Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
To address this challenge, we propose a hybrid imitation and reinforcement learning method, with which a dialogue agent can effectively learn from its interaction with users by learning from human teaching and feedback.
DIALOGUE STATE TRACKING IMITATION LEARNING TASK-ORIENTED DIALOGUE SYSTEMS