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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 2876–2900 of 4002 papers

TitleStatusHype
Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings—0
Misspelling Correction with Pre-trained Contextual Language Model—0
Mitigating Gender Bias in Contextual Word Embeddings—0
Mitigating Political Bias in Language Models Through Reinforced Calibration—0
MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network—0
MITRE: Seven Systems for Semantic Similarity in Tweets—0
Mixed Membership Word Embeddings for Computational Social Science—0
Mixing syntagmatic and paradigmatic information for concept detection—0
Mixtures of Deep Neural Experts for Automated Speech Scoring—0
Model-based Word Embeddings from Decompositions of Count Matrices—0
Model Choices Influence Attributive Word Associations: A Semi-supervised Analysis of Static Word Embeddings—0
Model-Free Context-Aware Word Composition—0
Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding—0
Modeling Noisiness to Recognize Named Entities using Multitask Neural Networks on Social Media—0
Modeling Order in Neural Word Embeddings at Scale—0
Modeling Personal Biases in Language Use by Inducing Personalized Word Embeddings—0
Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach—0
Modeling Tension in Stories via Commonsense Reasoning and Emotional Word Embeddings—0
Modeling Text using the Continuous Space Topic Model with Pre-Trained Word Embeddings—0
Modeling the Non-Substitutability of Multiword Expressions with Distributional Semantics and a Log-Linear Model—0
Modeling with Recurrent Neural Networks for Open Vocabulary Slots—0
Modelling metaphor with attribute-based semantics—0
Modelling Multi-modal Cross-interaction for ML-FSIC Based on Local Feature Selection—0
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks—0
Modelling Representation Noise in Emotion Analysis using Gaussian Processes—0
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