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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 2276–2300 of 4002 papers

TitleStatusHype
Enhancing Clinical Concept Extraction with Contextual Embeddings—0
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space ModelCode0
Learned In Speech Recognition: Contextual Acoustic Word Embeddings—0
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media—0
Contextual Word Representations: A Contextual IntroductionCode1
Categorical Metadata Representation for Customized Text ClassificationCode0
Wasserstein Barycenter Model EnsemblingCode0
Word embeddings for idiolect identification—0
Humor in Word Embeddings: Cockamamie Gobbledegook for NincompoopsCode0
Multi-task Learning for Target-dependent Sentiment ClassificationCode0
Word Embeddings for Entity-annotated TextsCode0
A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases—0
Understanding Composition of Word Embeddings via Tensor DecompositionCode0
Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey—0
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some MisconceptionsCode0
A Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings—0
Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements—0
No Training Required: Exploring Random Encoders for Sentence ClassificationCode0
Evaluating Word Embedding Models: Methods and Experimental Results—0
Analogies Explained: Towards Understanding Word Embeddings—0
Word Embeddings: A Survey—0
MORTY Embedding: Improved Embeddings without Supervision—0
Context-Sensitive Malicious Spelling Error Correction—0
Equalizing Gender Biases in Neural Machine Translation with Word Embeddings TechniquesCode0
Deconstructing Word Embeddings—0
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