most citedDistributed Structured Actor-Critic Reinforcement Learning for Universal Dialogue Management

13 citations · 46 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CL202011 cited

CREDIT: Coarse-to-Fine Sequence Generation for Dialogue State Tracking

Zhi Chen, Lu Chen, Zihan Xu +3

In dialogue systems, a dialogue state tracker aims to accurately find a compact representation of the current dialogue status, based on the entire dialogue history. While previous…

cs.CL2020

Dual Learning for Dialogue State Tracking

Zhi Chen, Lu Chen, Yanbin Zhao +2

In task-oriented multi-turn dialogue systems, dialogue state refers to a compact representation of the user goal in the context of dialogue history. Dialogue state tracking (DST) i…

cs.CL20202 cited

Structured Hierarchical Dialogue Policy with Graph Neural Networks

Zhi Chen, Xiaoyuan Liu, Lu Chen +1

Dialogue policy training for composite tasks, such as restaurant reservation in multiple places, is a practically important and challenging problem. Recently, hierarchical deep rei…

cs.CL202013 cited

Distributed Structured Actor-Critic Reinforcement Learning for Universal Dialogue Management

Zhi Chen, Lu Chen, Xiaoyuan Liu +1

The task-oriented spoken dialogue system (SDS) aims to assist a human user in accomplishing a specific task (e.g., hotel booking). The dialogue management is a core part of SDS. Th…

cs.CL2020

Deep Reinforcement Learning for On-line Dialogue State Tracking

Zhi Chen, Lu Chen, Xiang Zhou +1

Dialogue state tracking (DST) is a crucial module in dialogue management. It is usually cast as a supervised training problem, which is not convenient for on-line optimization. In…

cs.CL202011 cited

Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding

Su Zhu, Ruisheng Cao, Lu Chen +1

Few-shot slot tagging becomes appealing for rapid domain transfer and adaptation, motivated by the tremendous development of conversational dialogue systems. In this paper, we prop…