120 citations · 199 across the 7 of their papers we have counts for
7 papers
Conversational Semantic Parsing for Dialog State Tracking
Jianpeng Cheng, Devang Agrawal, Hector Martinez Alonso +12
We consider a new perspective on dialog state tracking (DST), the task of estimating a user's goal through the course of a dialog. By formulating DST as a semantic parsing task ove…
Active Learning for Domain Classification in a Commercial Spoken Personal Assistant
Xi C. Chen, Adithya Sagar, Justine T. Kao +5
We describe a method for selecting relevant new training data for the LSTM-based domain selection component of our personal assistant system. Adding more annotated training data fo…
NAIL: A General Interactive Fiction Agent
Matthew Hausknecht, Ricky Loynd, Greg Yang +2
Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Te…
Learning to Globally Edit Images with Textual Description
Hai Wang, Jason D. Williams, SingBing Kang
We show how we can globally edit images using textual instructions: given a source image and a textual instruction for the edit, generate a new image transformed under this instruc…
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Jason D. Williams, Kavosh Asadi, Geoffrey Zweig
End-to-end learning of recurrent neural networks (RNNs) is an attractive solution for dialog systems; however, current techniques are data-intensive and require thousands of dialog…
Sample-efficient Deep Reinforcement Learning for Dialog Control
Kavosh Asadi, Jason D. Williams
Representing a dialog policy as a recurrent neural network (RNN) is attractive because it handles partial observability, infers a latent representation of state, and can be optimiz…