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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 601–625 of 4002 papers

TitleStatusHype
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations—0
Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense EmbeddingsCode0
VAST: The Valence-Assessing Semantics Test for Contextualizing Language ModelsCode0
Survey on Automated Short Answer Grading with Deep Learning: from Word Embeddings to Transformers—0
Semi-constraint Optimal Transport for Entity Alignment with Dangling CasesCode1
Using Word Embeddings to Analyze Protests News—0
TextConvoNet:A Convolutional Neural Network based Architecture for Text Classification—0
Unsupervised Alignment of Distributional Word Embeddings—0
Plumeria at SemEval-2022 Task 6: Robust Approaches for Sarcasm Detection for English and Arabic Using Transformers and Data AugmentationCode0
Automated Single-Label Patent Classification using Ensemble Classifiers—0
Representing Mixtures of Word Embeddings with Mixtures of Topic EmbeddingsCode0
Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR ErrorsCode1
Topological Data Analysis for Word Sense Disambiguation—0
SemSup: Semantic Supervision for Simple and Scalable Zero-shot GeneralizationCode0
Prediction of Depression Severity Based on the Prosodic and Semantic Features with Bidirectional LSTM and Time Distributed CNN—0
Self-Attention for Incomplete Utterance Rewriting—0
Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval—0
Sobolev Transport: A Scalable Metric for Probability Measures with Graph MetricsCode0
Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge—0
Contextual Semantic Embeddings for Ontology Subsumption PredictionCode2
Data-Driven Mitigation of Adversarial Text Perturbation—0
Selection Strategies for Commonsense Knowledge—0
Word Embeddings for Automatic Equalization in Audio MixingCode1
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision—0
Regional Differences in Information Privacy Concerns After the Facebook-Cambridge Analytica Data Scandal—0
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