output
20132026
most citedDCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

325 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2022★ 11 cited

Integrating Lattice-Free MMI into End-to-End Speech Recognition

Jinchuan Tian, Jianwei Yu, Chao Weng +2

In automatic speech recognition (ASR) research, discriminative criteria have achieved superior performance in DNN-HMM systems. Given this success, the adoption of discriminative cr…

cs.CL2021

Semantic Representation for Dialogue Modeling

Xuefeng Bai, Yulong Chen, Linfeng Song +1

Although neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities. T…

cs.CL2021★ 3 cited

Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge

Yang Deng, Yuexiang Xie, Yaliang Li +3

Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in pra…

cs.CL2021

Conversational Semantic Role Labeling

Kun Xu, Han Wu, Linfeng Song +3

Semantic role labeling (SRL) aims to extract the arguments for each predicate in an input sentence. Traditional SRL can fail to analyze dialogues because it only works on every sin…

cs.CL2020★ 26 cited

Learning with Weak Supervision for Email Intent Detection

Kai Shu, Subhabrata Mukherjee, Guoqing Zheng +3

Email remains one of the most frequently used means of online communication. People spend a significant amount of time every day on emails to exchange information, manage tasks and…

cs.CL2020★ 10 cited

Logical Natural Language Generation from Open-Domain Tables

Wenhu Chen, Jianshu Chen, Yu Su +2

Neural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence. However, existing studies on neural NLG are primarily focused on s…