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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 2951–2975 of 4002 papers

TitleStatusHype
Regionalized models for Spanish language variations based on Twitter—0
A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings—0
A Lexicalized Tree Kernel for Open Information Extraction—0
Aligning Open IE Relations and KB Relations using a Siamese Network Based on Word Embedding—0
Aligning Opinions: Cross-Lingual Opinion Mining with Dependencies—0
Aligning Very Small Parallel Corpora Using Cross-Lingual Word Embeddings and a Monogamy Objective—0
Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning—0
Alignment-free Cross-lingual Semantic Role Labeling—0
A Linear Dynamical System Model for Text—0
A Linguistically Informed Convolutional Neural Network—0
All-In-1 at IJCNLP-2017 Task 4: Short Text Classification with One Model for All Languages—0
All That Glitters is Not Gold: A Gold Standard of Adjective-Noun Collocations for German—0
All-words Word Sense Disambiguation Using Concept Embeddings—0
A Locally Linear Procedure for Word Translation—0
A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic—0
A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation—0
A Methodology for Studying Linguistic and Cultural Change in China, 1900-1950—0
A Minimalist Approach to Shallow Discourse Parsing and Implicit Relation Recognition—0
A Mixture Model for Learning Multi-Sense Word Embeddings—0
Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification—0
A Model of Zero-Shot Learning of Spoken Language Understanding—0
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages—0
A Morpho-Syntactically Informed LSTM-CRF Model for Named Entity Recognition—0
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