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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 3701–3725 of 4002 papers

TitleStatusHype
Do Not Harm Protected Groups in Debiasing Language Representation Models—0
Do not neglect related languages: The case of low-resource Occitan cross-lingual word embeddings—0
Don't Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects—0
DoTheMath at SemEval-2020 Task 12 : Deep Neural Networks with Self Attention for Arabic Offensive Language Detection—0
Do We Need Neural Models to Explain Human Judgments of Acceptability?—0
The Influence of Down-Sampling Strategies on SVD Word Embedding Stability—0
Do Word Embeddings Really Understand Loughran-McDonald's Polarities?—0
Drop-out Conditional Random Fields for Twitter with Huge Mined Gazetteer—0
DS at SemEval-2019 Task 9: From Suggestion Mining with neural networks to adversarial cross-domain classification—0
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations—0
DSTC8-AVSD: Multimodal Semantic Transformer Network with Retrieval Style Word Generator—0
Dual Embeddings and Metrics for Relational Similarity—0
Dual Tensor Model for Detecting Asymmetric Lexico-Semantic Relations—0
Du bon usage d'ingr\'edients linguistiques sp\'eciaux pour classer des recettes exceptionnelles (Using Special Linguistic Ingredients to Classify Exceptional Recipes )—0
Dyr Bul Shchyl. Proxying Sound Symbolism With Word Embeddings—0
Early Discovery of Disappearing Entities in Microblogs—0
Earth Mover's Distance Minimization for Unsupervised Bilingual Lexicon Induction—0
Easy-First Dependency Parsing with Hierarchical Tree LSTMs—0
ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification—0
ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection—0
ECNU: Leveraging Word Embeddings to Boost Performance for Paraphrase in Twitter—0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation—0
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