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Chinese Word Segmentation

Chinese word segmentation is the task of splitting Chinese text (i.e. a sequence of Chinese characters) into words (Source: www.nlpprogress.com).

Papers

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Showing 76–100 of 244 papers

TitleStatusHype
A Seq-to-Seq Transformer Premised Temporal Convolutional Network for Chinese Word Segmentation—0
A realistic and robust model for Chinese word segmentation—0
Is Word Segmentation Necessary for Deep Learning of Chinese Representations?—0
Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization—0
A Graph-based Model for Joint Chinese Word Segmentation and Dependency ParsingCode0
Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning—0
Improving Cross-Domain Chinese Word Segmentation with Word EmbeddingsCode0
Glyce: Glyph-vectors for Chinese Character RepresentationsCode0
Chinese Word Segmentation: Another Decade Review (2007-2017)—0
Robust Chinese Word Segmentation with Contextualized Word Representations—0
Switch-LSTMs for Multi-Criteria Chinese Word Segmentation—0
Hyperbolic Deep Learning for Chinese Natural Language Understanding—0
LSICC: A Large Scale Informal Chinese CorpusCode1
Fast Neural Chinese Word Segmentation for Long Sentences—0
Subword Encoding in Lattice LSTM for Chinese Word SegmentationCode0
Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent NetworksCode0
Unsupervised Neural Word Segmentation for Chinese via Segmental Language ModelingCode0
An Empirical Study of Machine Translation for the Shared Task of WMT18—0
Sanskrit Sandhi Splitting using seq2(seq)2—0
Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention MechanismCode0
AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale—0
State-of-the-art Chinese Word Segmentation with Bi-LSTMsCode0
Multiple Character Embeddings for Chinese Word Segmentation—0
Adaptive Multi-Task Transfer Learning for Chinese Word Segmentation in Medical TextCode0
From Chinese Word Segmentation to Extraction of Constructions: Two Sides of the Same Algorithmic Coin—0
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