113 citations · 454 across the 27 of their papers we have counts for
6 papers · 1 filter
Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understanding
Bing Liu, Ian Lane
The goal of this paper is to learn cross-domain representations for slot filling task in spoken language understanding (SLU). Most of the recently published SLU models are domain-s…
End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learning
Bing Liu, Gokhan Tur, Dilek Hakkani-Tur +2
In this paper, we present a neural network based task-oriented dialogue system that can be optimized end-to-end with deep reinforcement learning (RL). The system is able to track d…
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models
Bing Liu, Tong Yu, Ian Lane +1
Dialog response selection is an important step towards natural response generation in conversational agents. Existing work on neural conversational models mainly focuses on offline…
Iterative Policy Learning in End-to-End Trainable Task-Oriented Neural Dialog Models
Bing Liu, Ian Lane
In this paper, we present a deep reinforcement learning (RL) framework for iterative dialog policy optimization in end-to-end task-oriented dialog systems. Popular approaches in le…
An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog
Bing Liu, Ian Lane
We present a novel end-to-end trainable neural network model for task-oriented dialog systems. The model is able to track dialog state, issue API calls to knowledge base (KB), and…
Dialog Context Language Modeling with Recurrent Neural Networks
Bing Liu, Ian Lane
In this work, we propose contextual language models that incorporate dialog level discourse information into language modeling. Previous works on contextual language model treat pr…