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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 1751–1775 of 4002 papers

TitleStatusHype
Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing—0
Analysis of Italian Word Embeddings—0
Contextualized Embeddings for Enriching Linguistic Analyses on Politeness—0
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects—0
How to represent a word and predict it, too: Improving tied architectures for language modelling—0
Contextualized moral inference—0
How Well Can We Predict Hypernyms from Word Embeddings? A Dataset-Centric Analysis—0
Human-in-the-Loop Refinement of Word Embeddings—0
HumorHawk at SemEval-2017 Task 6: Mixing Meaning and Sound for Humor Recognition—0
Contextualized Word Embeddings Encode Aspects of Human-Like Word Sense Knowledge—0
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning—0
"Hunt Takes Hare": Theming Games Through Game-Word Vector Translation—0
Improving Disfluency Detection by Self-Training a Self-Attentive Model—0
Improving Translation of Out Of Vocabulary Words using Bilingual Lexicon Induction in Low-Resource Machine Translation—0
Hybridation d'un agent conversationnel avec des plongements lexicaux pour la formation au diagnostic m\'edical (Hybridization of a conversational agent with word embeddings for medical diagnostic training)—0
Hybrid Code Networks using a convolutional neural network as an input layer achieves higher turn accuracy—0
Des pseudo-sens pour am\'eliorer l'extraction de synonymes \`a partir de plongements lexicaux (Pseudo-senses for improving the extraction of synonyms from word embeddings)—0
Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes—0
Hyperbolic Centroid Calculations for Text Classification—0
Designing a Russian Idiom-Annotated Corpus—0
BERTrade: Using Contextual Embeddings to Parse Old French—0
Hypothesis Testing based Intrinsic Evaluation of Word Embeddings—0
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification—0
ICL-HD at SemEval-2016 Task 10: Improving the Detection of Minimal Semantic Units and their Meanings with an Ontology and Word Embeddings—0
BERTMap: A BERT-based Ontology Alignment System—0
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