most citedCREDIT: Coarse-to-Fine Sequence Generation for Dialogue State Tracking

11 citations · 22 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL20219 cited

LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations

Ruisheng Cao, Lu Chen, Zhi Chen +3

This work aims to tackle the challenging heterogeneous graph encoding problem in the text-to-SQL task. Previous methods are typically node-centric and merely utilize different weig…

cs.CL20211 cited

ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser

Zhi Chen, Lu Chen, Yanbin Zhao +4

Given a database schema, Text-to-SQL aims to translate a natural language question into the corresponding SQL query. Under the setup of cross-domain, traditional semantic parsing m…

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.CL2020

Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing

Ruisheng Cao, Su Zhu, Chenyu Yang +5

One daunting problem for semantic parsing is the scarcity of annotation. Aiming to reduce nontrivial human labor, we propose a two-stage semantic parsing framework, where the first…

cs.CL20201 cited

Semi-Supervised Text Simplification with Back-Translation and Asymmetric Denoising Autoencoders

Yanbin Zhao, Lu Chen, Zhi Chen +1

Text simplification (TS) rephrases long sentences into simplified variants while preserving inherent semantics. Traditional sequence-to-sequence models heavily rely on the quantity…