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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 976–1000 of 4002 papers

TitleStatusHype
From Fully Trained to Fully Random Embeddings: Improving Neural Machine Translation with Compact Word Embedding Tables—0
Frequency-based Distortions in Contextualized Word Embeddings—0
A multilabel approach to morphosyntactic probing—0
Sentence Alignment with Parallel Documents Facilitates Biomedical Machine TranslationCode0
Multi-source Neural Topic Modeling in Multi-view Embedding SpacesCode0
Embodying Pre-Trained Word Embeddings Through Robot Actions—0
Word2rate: training and evaluating multiple word embeddings as statistical transitions—0
"Wikily" Supervised Neural Translation Tailored to Cross-Lingual TasksCode0
Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task TrainingCode0
[RE] Double-Hard Debias: Tailoring Word Embeddings for Gender Bias MitigationCode0
UPB at SemEval-2021 Task 1: Combining Deep Learning and Hand-Crafted Features for Lexical Complexity Prediction—0
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based ApproachCode0
Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoders—0
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
The DKU System Description for The Interspeech 2021 Auto-KWS Challenge—0
Object Priors for Classifying and Localizing Unseen ActionsCode0
FreSaDa: A French Satire Data Set for Cross-Domain Satire DetectionCode0
Machine Learning Based on Natural Language Processing to Detect Cardiac Failure in Clinical Narratives—0
Probing BERT in Hyperbolic SpacesCode1
Statistically significant detection of semantic shifts using contextual word embeddings—0
Revisiting Simple Neural Probabilistic Language ModelsCode1
Combining Pre-trained Word Embeddings and Linguistic Features for Sequential Metaphor Identification—0
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word RepresentationsCode1
Query2Prod2Vec Grounded Word Embeddings for eCommerceCode1
Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings—0
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