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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 1026–1050 of 4002 papers

TitleStatusHype
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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