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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 126–150 of 4002 papers

TitleStatusHype
MT2ST: Adaptive Multi-Task to Single-Task LearningCode1
All Word Embeddings from One EmbeddingCode1
ALL-IN-1: Short Text Classification with One Model for All LanguagesCode1
Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM NetworkCode1
Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency DetectionCode1
Can a Fruit Fly Learn Word Embeddings?Code1
AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic LanguagesCode1
Affective and Contextual Embedding for Sarcasm DetectionCode1
A Comprehensive Analysis of Static Word Embeddings for TurkishCode1
Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer GradingCode1
Compass-aligned Distributional Embeddings for Studying Semantic Differences across CorporaCode1
GLOW : Global Weighted Self-Attention Network for Web SearchCode1
ALIGN-MLM: Word Embedding Alignment is Crucial for Multilingual Pre-trainingCode1
Brain2Word: Decoding Brain Activity for Language GenerationCode1
Contextualized Embeddings based Transformer Encoder for Sentence Similarity Modeling in Answer Selection TaskCode1
Contextual Word Representations: A Contextual IntroductionCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
Circumventing Concept Erasure Methods For Text-to-Image Generative ModelsCode1
Cycle Text-To-Image GAN with BERTCode1
Debiasing Pre-trained Contextualised EmbeddingsCode1
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual RepresentationsCode1
A Neural Few-Shot Text Classification Reality CheckCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
DeFINE: DEep Factorized INput Token Embeddings for Neural Sequence ModelingCode1
Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon InductionCode1
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