One Classifier for All Ambiguous Words: Overcoming Data Sparsity by Utilizing Sense Correlations Across Words

LREC 2020 • Prafulla Kumar Choubey • Ruihong Huang

Most supervised word sense disambiguation (WSD) systems build word-specific classifiers by leveraging labeled data. However, when using word-specific classifiers, the sparseness of annotations leads to inferior sense disambiguation performance on less frequently seen words... (read more)

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METHOD	TYPE
Sigmoid Activation	Activation Functions
Weight Decay	Regularization
Softmax	Output Functions
Tanh Activation	Activation Functions
Adam	Stochastic Optimization
LSTM	Recurrent Neural Networks
Multi-Head Attention	Attention Modules
Dropout	Regularization
GELU	Activation Functions
Attention Dropout	Regularization
Linear Warmup With Linear Decay	Learning Rate Schedules
Dense Connections	Feedforward Networks
Layer Normalization	Normalization
Scaled Dot-Product Attention	Attention Mechanisms
GloVe	Word Embeddings
WordPiece	Subword Segmentation
Residual Connection	Skip Connections
BERT	Language Models
BiLSTM	Bidirectional Recurrent Neural Networks
ELMo	Word Embeddings

METHOD

TYPE

Sigmoid Activation