2 citations · 4 across the 3 of their papers we have counts for
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cs.CL2018
Language Modeling with Sparse Product of Sememe Experts
Yihong Gu, Jun Yan, Hao Zhu +5
Most language modeling methods rely on large-scale data to statistically learn the sequential patterns of words. In this paper, we argue that words are atomic language units but no…
cs.CL2018
Hierarchical Neural Network for Extracting Knowledgeable Snippets and Documents
Ganbin Zhou, Rongyu Cao, Xiang Ao +4
In this study, we focus on extracting knowledgeable snippets and annotating knowledgeable documents from Web corpus, consisting of the documents from social media and We-media. Inf…
cs.CL2018
Incorporating Chinese Characters of Words for Lexical Sememe Prediction
Huiming Jin, Hao Zhu, Zhiyuan Liu +4
Sememes are minimum semantic units of concepts in human languages, such that each word sense is composed of one or multiple sememes. Words are usually manually annotated with their…