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20162022
most citedEnd-to-end spoofing detection with raw waveform CLDNNs

67 citations · 216 across the 25 of their papers we have counts for

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28 papers · 1 filter

cs.CL20221 cited

OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue

Zhi Chen, Yuncong Liu, Lu Chen +3

This paper presents an ontology-aware pretrained language model (OPAL) for end-to-end task-oriented dialogue (TOD). Unlike chit-chat dialogue models, task-oriented dialogue models…

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.CL20213 cited

Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL

Zhi Chen, Lu Chen, Hanqi Li +4

Recently, Text-to-SQL for multi-turn dialogue has attracted great interest. Here, the user input of the current turn is parsed into the corresponding SQL query of the appropriate d…

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.CL2021

LET: Linguistic Knowledge Enhanced Graph Transformer for Chinese Short Text Matching

Boer Lyu, Lu Chen, Su Zhu +1

Chinese short text matching is a fundamental task in natural language processing. Existing approaches usually take Chinese characters or words as input tokens. They have two limita…

cs.CL2020

An Investigation on Different Underlying Quantization Schemes for Pre-trained Language Models

Zihan Zhao, Yuncong Liu, Lu Chen +3

Recently, pre-trained language models like BERT have shown promising performance on multiple natural language processing tasks. However, the application of these models has been li…