160 citations · 344 across the 8 of their papers we have counts for
6 papers · 1 filter
Grounding Open-Domain Instructions to Automate Web Support Tasks
Nancy Xu, Sam Masling, Michael Du +4
Grounding natural language instructions on the web to perform previously unseen tasks enables accessibility and automation. We introduce a task and dataset to train AI agents from…
Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
Bing Liu, Gokhan Tur, Dilek Hakkani-Tur +2
In this work, we present a hybrid learning method for training task-oriented dialogue systems through online user interactions. Popular methods for learning task-oriented dialogues…
Scalable Multi-Domain Dialogue State Tracking
Abhinav Rastogi, Dilek Hakkani-Tur, Larry Heck
Dialogue state tracking (DST) is a key component of task-oriented dialogue systems. DST estimates the user's goal at each user turn given the interaction until then. State of the a…
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…
Leveraging Semantic Web Search and Browse Sessions for Multi-Turn Spoken Dialog Systems
Lu Wang, Larry Heck, Dilek Hakkani-Tur
Training statistical dialog models in spoken dialog systems (SDS) requires large amounts of annotated data. The lack of scalable methods for data mining and annotation poses a sign…
Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation
Hongzhao Huang, Larry Heck, Heng Ji
Entity Disambiguation aims to link mentions of ambiguous entities to a knowledge base (e.g., Wikipedia). Modeling topical coherence is crucial for this task based on the assumption…