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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 1001–1050 of 4002 papers

TitleStatusHype
Multi-task Learning Using a Combination of Contextualised and Static Word Embeddings for Arabic Sarcasm Detection and Sentiment Analysis—0
Country-level Arabic Dialect Identification Using Small Datasets with Integrated Machine Learning Techniques and Deep Learning Models—0
Eliciting Explicit Knowledge From Domain Experts in Direct Intrinsic Evaluation of Word Embeddings for Specialized DomainsCode0
Using contextual and cross-lingual word embeddings to improve variety in template-based NLG for automated journalism—0
Cross-Lingual Transfer Learning for Hate Speech Detection—0
RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding—0
Semantic-aware transformation of short texts using word embeddings: An application in the Food Computing domain—0
Exploiting Position and Contextual Word Embeddings for Keyphrase Extraction from Scientific Papers—0
The Chinese Remainder Theorem for Compact, Task-Precise, Efficient and Secure Word Embeddings—0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa - A Large Romanian Sentiment Data Set—0
Handling Out-Of-Vocabulary Problem in Hangeul Word Embeddings—0
NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter AccessCode1
Evaluating Neural Word Embeddings for SanskritCode0
Self-Supervised Euphemism Detection and Identification for Content ModerationCode1
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Locally-Contextual Nonlinear CRFs for Sequence Labeling—0
Probabilistic Analogical Mapping with Semantic Relation Networks—0
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications—0
Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP ModelsCode1
An Introduction to Robust Graph Convolutional Networks—0
When Word Embeddings Become Endangered—0
Monolingual and Parallel Corpora for Kangri Low Resource LanguageCode0
SparseGAN: Sparse Generative Adversarial Network for Text Generation—0
SEMIE: SEMantically Infused Embeddings with Enhanced Interpretability for Domain-specific Small Corpus—0
Attention-based model for predicting question relatedness on Stack Overflow—0
Acoustic word embeddings for zero-resource languages using self-supervised contrastive learning and multilingual adaptationCode0
Do Word Embeddings Really Understand Loughran-McDonald's Polarities?—0
DeepHate: Hate Speech Detection via Multi-Faceted Text Representations—0
Cooperative Self-training of Machine Reading ComprehensionCode1
Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist NewspapersCode0
Towards Multi-Sense Cross-Lingual Alignment of Contextual EmbeddingsCode0
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding SpacesCode0
Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddings—0
Evaluation of Morphological Embeddings for the Russian Language—0
CNN-based Spoken Term Detection and Localization without Dynamic Programming—0
A Comparison of Word2Vec, HMM2Vec, and PCA2Vec for Malware Classification—0
Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning—0
Overcoming Poor Word Embeddings with Word Definitions—0
WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word EmbeddingsCode1
Lex2vec: making Explainable Word Embeddings via Lexical Resources—0
CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning—0
Spanish Biomedical and Clinical Language Embeddings—0
Abelian Neural Networks—0
The Sensitivity of Word Embeddings-based Author Detection Models to Semantic-preserving Adversarial Perturbations—0
Paraphrases do not explain word analogiesCode0
Co-occurrences using Fasttext embeddings for word similarity tasks in UrduCode0
Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentation—0
Knowledge-Base Enriched Word Embeddings for Biomedical Domain—0
Towards Emotion Recognition in Hindi-English Code-Mixed Data: A Transformer Based ApproachCode0
Revisiting Language Encoding in Learning Multilingual RepresentationsCode1
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