22 citations · 72 across the 14 of their papers we have counts for
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cs.CL2020★ 22 cited
Fast and Accurate Neural CRF Constituency Parsing
Yu Zhang, Houquan Zhou, Zhenghua Li
Estimating probability distribution is one of the core issues in the NLP field. However, in both deep learning (DL) and pre-DL eras, unlike the vast applications of linear-chain CR…
cs.CL2020★ 7 cited
Efficient Second-Order TreeCRF for Neural Dependency Parsing
Yu Zhang, Zhenghua Li, Min Zhang
In the deep learning (DL) era, parsing models are extremely simplified with little hurt on performance, thanks to the remarkable capability of multi-layer BiLSTMs in context repres…
cs.CL2020★ 7 cited
Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?
Houquan Zhou, Yu Zhang, Zhenghua Li +1
In the pre deep learning era, part-of-speech tags have been considered as indispensable ingredients for feature engineering in dependency parsing. But quite a few works focus on jo…