Task-Oriented Dialogue Systems
121 papers with code • 4 benchmarks • 19 datasets
Achieving a pre-defined task through a dialog.
Benchmarks
These leaderboards are used to track progress in Task-Oriented Dialogue Systems
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Libraries
Use these libraries to find Task-Oriented Dialogue Systems models and implementations
MultiWOZ
SGD
MuTual
CrossWOZ
ABCD
BiToD
Most implemented papers
Domain Transfer in Dialogue Systems without Turn-Level Supervision
Task oriented dialogue systems rely heavily on specialized dialogue state tracking (DST) modules for dynamically predicting user intent throughout the conversation.
Conditioned Query Generation for Task-Oriented Dialogue Systems
snipsco/automatic-data-generation
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Scarcity of training data for task-oriented dialogue systems is a well known problem that is usually tackled with costly and time-consuming manual data annotation.
Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems
zliucr/mixed-language-training
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Recently, data-driven task-oriented dialogue systems have achieved promising performance in English.
Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems
In task-oriented dialogue systems the dialogue state tracker (DST) component is responsible for predicting the state of the dialogue based on the dialogue history.
ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems
thu-coai/ConvLab-2
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ACL 2020
We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.
MuTual: A Dataset for Multi-Turn Dialogue Reasoning
Non-task oriented dialogue systems have achieved great success in recent years due to largely accessible conversation data and the development of deep learning techniques.
From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap
saketdingliwal/Few-Shot-DST
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WS 2020
In this paper, we propose using machine reading comprehension (RC) in state tracking from two perspectives: model architectures and datasets.
Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog
However, there has been relatively little research on how to effectively use data from all domains to improve the performance of each domain and also unseen domains.
Multi-Domain Dialogue Acts and Response Co-Generation
InitialBug/MarCo-Dialog
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ACL 2020
Unlike those pipeline approaches, our act generation module preserves the semantic structures of multi-domain dialogue acts and our response generation module dynamically attends to different acts as needed.
ConfNet2Seq: Full Length Answer Generation from Spoken Questions
kolk/ConfnetPointerGenBaseline
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This is the first attempt towards generating full-length natural answers from a graph input(confusion network) to the best of our knowledge.
