Large-scale conversational systems typically rely on a skill-routing
com...
Open world classification is a task in natural language processing with ...
Conversational understanding is an integral part of modern intelligent
d...
Recently, self-learning methods based on user satisfaction metrics and
c...
Graph neural networks (GNNs) have achieved remarkable success in recomme...
Generating representations that precisely reflect customers' behavior is...
Skill routing is an important component in large-scale conversational
sy...
In many real-world machine learning applications, samples belong to a se...
A large-scale conversational agent can suffer from understanding user
ut...
Natural Language Generation (NLG) is a key component in a task-oriented
...
Real-world machine learning systems are achieving remarkable performance...
We have been witnessing the usefulness of conversational AI systems such...
Current state-of-the-art large-scale conversational AI or intelligent di...
The evaluation of multi-turn dialogues remains challenging. The common
a...
Natural Language Understanding (NLU) is an established component within ...
Turn-level user satisfaction is one of the most important performance me...
Measuring user satisfaction level is a challenging task, and a critical
...
Reinforcement-based training methods have emerged as the most popular ch...
This paper introduces the Eighth Dialog System Technology Challenge. In ...
Ambiguous user queries in search engines result in the retrieval of docu...
Goal-oriented dialogue systems are now being widely adopted in industry ...
Generating responses in a targeted style is a useful yet challenging tas...
Learning with minimal data is one of the key challenges in the developme...
Neural dialog models often lack robustness to anomalous user input and
p...
We present ConvLab, an open-source multi-domain end-to-end dialog system...
Generating responses that are consistent with the dialogue context is on...
Although recent neural conversation models have shown great potential, t...
Neural network-based dialog models often lack robustness to anomalous,
o...
Neural conversation models are attractive because one can train a model
...
Conversational agents such as Alexa and Google Assistant constantly need...
In practice, most spoken language understanding systems process user inp...
While end-to-end neural conversation models have led to promising advanc...
In multi-turn dialogs, natural language understanding models can introdu...
Building a dialogue agent to fulfill complex tasks, such as travel plann...