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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 2201–2225 of 4002 papers

TitleStatusHype
Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations—0
Learning Embeddings into Entropic Wasserstein SpacesCode0
Models in the Wild: On Corruption Robustness of NLP Systems—0
A Typedriven Vector Semantics for Ellipsis with Anaphora using Lambek Calculus with Limited Contraction—0
HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word EmbeddingsCode0
Pretrained Transformers for Simple Question Answering—0
Predicting Word Concreteness and Imagery—0
Poincare Glove: Hyperbolic Word EmbeddingsCode0
A Comparison of Context-sensitive Models for Lexical Substitution—0
Learning Mixed-Curvature Representations in Product Spaces—0
Aligning Open IE Relations and KB Relations using a Siamese Network Based on Word Embedding—0
Language-Agnostic Model for Aspect-Based Sentiment Analysis—0
Investigating the Stability of Concrete Nouns in Word Embeddings—0
On Learning Word Embeddings From Linguistically Augmented Text Corpora—0
RelWalk -- A Latent Variable Model Approach to Knowledge Graph Embedding—0
Distribution is not enough: going Firther—0
Semantic Frame Embeddings for Detecting Relations between Software Requirements—0
Words are Vectors, Dependencies are Matrices: Learning Word Embeddings from Dependency Graphs—0
Wasserstein Barycenter Model Ensembling—0
The Effectiveness of Pre-Trained Code Embeddings—0
Unsupervised Hyper-alignment for Multilingual Word Embeddings—0
Nested Variational Autoencoder for Topic Modeling on Microtexts with Word VectorsCode0
Zero-training Sentence Embedding via Orthogonal BasisCode0
Detecting Paraphrases of Standard Clause Titles in Insurance Contracts—0
Encoding Category Trees Into Word-Embeddings Using Geometric ApproachCode0
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