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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 51–100 of 244 papers

TitleStatusHype
RethinkCWS: Is Chinese Word Segmentation a Solved Task?Code1
Semi-supervised URL Segmentation with Recurrent Neural NetworksPre-trained on Knowledge Graph EntitiesCode1
A Joint Multiple Criteria Model in Transfer Learning for Cross-domain Chinese Word Segmentation—0
Pre-training with Meta Learning for Chinese Word Segmentation—0
A Joint Model for Graph-based Chinese Dependency Parsing—0
N-LTP: An Open-source Neural Language Technology Platform for ChineseCode3
fastHan: A BERT-based Multi-Task Toolkit for Chinese NLPCode1
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation TaskCode0
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word SegmentationCode1
Neural Graph Matching Networks for Chinese Short Text Matching—0
Joint Chinese Word Segmentation and Part-of-speech Tagging via Two-way Attentions of Auto-analyzed KnowledgeCode1
Improving Chinese Word Segmentation with Wordhood Memory NetworksCode1
Incorporating Uncertain Segmentation Information into Chinese NER for Social Media Text—0
Unified Multi-Criteria Chinese Word Segmentation with BERT—0
Integrating Boundary Assembling into a DNN Framework for Named Entity Recognition in Chinese Social Media Text—0
A New Clustering neural network for Chinese word segmentation—0
Neural Chinese Word Segmentation as Sequence to Sequence TranslationCode0
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram RepresentationsCode1
Attention Is All You Need for Chinese Word SegmentationCode0
BERT Meets Chinese Word Segmentation—0
NE-LP: Normalized Entropy and Loss Prediction based Sampling for Active Learning in Chinese Word Segmentation on EHRs—0
Investigating Self-Attention Network for Chinese Word SegmentationCode0
A Concise Model for Multi-Criteria Chinese Word Segmentation with Transformer EncoderCode0
PKUSEG: A Toolkit for Multi-Domain Chinese Word SegmentationCode0
Shrinking Japanese Morphological Analyzers With Neural Networks and Semi-supervised Learning—0
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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