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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 1126–1150 of 4002 papers

TitleStatusHype
Neural Abstractive Multi-Document Summarization: Hierarchical or Flat Structure?—0
Explaining the Trump Gap in Social Distancing Using COVID Discourse—0
Leveraging Contextual Embeddings and Idiom Principle for Detecting Idiomaticity in Potentially Idiomatic Expressions—0
Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages—0
“Shakespeare in the Vectorian Age” – An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes—0
Graph-based Syntactic Word Embeddings—0
A Language-Based Approach to Fake News Detection Through Interpretable Features and BRNN—0
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity—0
Comparison between Voting Classifier and Deep Learning methods for Arabic Dialect Identification—0
Demonstration of a Literature Based Discovery System based on Ontologies, Semantic Filters and Word Embeddings for the Raynaud Disease-Fish Oil Rediscovery—0
MultiVitaminBooster at PARSEME Shared Task 2020: Combining Window- and Dependency-Based Features with Multilingual Contextualised Word Embeddings for VMWE Detection—0
Interdependencies of Gender and Race in Contextualized Word Embeddings—0
Argument from Old Man’s View: Assessing Social Bias in Argumentation—0
CLaC at SMM4H 2020: Birth Defect Mention Detection—0
Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings—0
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing—0
Unmasking Contextual Stereotypes: Measuring and Mitigating BERT’s Gender BiasCode1
Lexical Induction of Morphological and Orthographic Forms for Low-Resourced Languages—0
Go Simple and Pre-Train on Domain-Specific Corpora: On the Role of Training Data for Text Classification—0
Augmenting NLP models using Latent Feature Interpolations—0
A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown DetectionCode0
Expert Concept-Modeling Ground Truth Construction for Word Embeddings Evaluation in Concept-Focused DomainsCode0
Manifold Learning-based Word Representation Refinement Incorporating Global and Local Information—0
Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction—0
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation—0
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