24 citations · 30 across the 4 of their papers we have counts for
6 papers
Zero-Shot Dialogue State Tracking via Cross-Task Transfer
Zhaojiang Lin, Bing Liu, Andrea Madotto +8
Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data. In…
Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon +7
Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper,…
Continual Learning in Task-Oriented Dialogue Systems
Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou +6
Continual learning in task-oriented dialogue systems can allow us to add new domains and functionalities through time without incurring the high cost of a whole system retraining.…
Resource Constrained Dialog Policy Learning via Differentiable Inductive Logic Programming
Zhenpeng Zhou, Ahmad Beirami, Paul Crook +3
Motivated by the needs of resource constrained dialog policy learning, we introduce dialog policy via differentiable inductive logic (DILOG). We explore the tasks of one-shot learn…
Optimization of Molecules via Deep Reinforcement Learning
Zhenpeng Zhou, Steven Kearnes, Li Li +2
We present a framework, which we call Molecule Deep -Networks (MolDQN), for molecule optimization by combining domain knowledge of chemistry and state-of-the-art reinforcement l…
Graph Convolution: A High-Order and Adaptive Approach
Zhenpeng Zhou, Xiaocheng Li
In this paper, we presented a novel convolutional neural network framework for graph modeling, with the introduction of two new modules specially designed for graph-structured data…