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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 2251–2275 of 4002 papers

TitleStatusHype
Multi-Label Image Recognition with Graph Convolutional NetworksCode0
ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples—0
Exploring Fine-Tuned Embeddings that Model Intensifiers for Emotion Analysis—0
Effective Context and Fragment Feature Usage for Named Entity Recognition—0
Alternative Weighting Schemes for ELMo EmbeddingsCode0
Density Matching for Bilingual Word EmbeddingCode0
Text Classification Components for Detecting Descriptions and Names of CAD models—0
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems—0
Generative Adversarial Networks for text using word2vec intermediariesCode0
Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence LabelingCode0
Probing Biomedical Embeddings from Language ModelsCode0
Evaluating KGR10 Polish word embeddings in the recognition of temporal expressions using BiLSTM-CRF—0
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word EmbeddingsCode0
Identification, Interpretability, and Bayesian Word EmbeddingsCode0
Attentive Mimicking: Better Word Embeddings by Attending to Informative ContextsCode0
Adaptation of Hierarchical Structured Models for Speech Act Recognition in Asynchronous Conversation—0
Unsupervised Abbreviation Disambiguation Contextual disambiguation using word embeddings—0
Multimodal Machine Translation with Embedding PredictionCode0
SART - Similarity, Analogies, and Relatedness for Tatar Language: New Benchmark Datasets for Word Embeddings EvaluationCode0
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition—0
Integrating Semantic Knowledge to Tackle Zero-shot Text ClassificationCode0
Learning semantic sentence representations from visually grounded language without lexical knowledgeCode0
Deep Learning and Word Embeddings for Tweet Classification for Crisis Response—0
On Measuring Social Biases in Sentence EncodersCode0
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue systemCode0
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