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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

Showing 11011150 of 4002 papers

TitleStatusHype
Introducing Orthogonal Constraint in Structural ProbesCode0
SemGloVe: Semantic Co-occurrences for GloVe from BERTCode0
Deriving Contextualised Semantic Features from BERT (and Other Transformer Model) Embeddings0
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence LearningCode1
DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali LanguageCode0
WEmbSim: A Simple yet Effective Metric for Image Captioning0
Improved Biomedical Word Embeddings in the Transformer EraCode0
BERT Goes Shopping: Comparing Distributional Models for Product RepresentationsCode1
Keyword-Guided Neural Conversational ModelCode1
Model Choices Influence Attributive Word Associations: A Semi-supervised Analysis of Static Word Embeddings0
Intrinsic Image Captioning Evaluation0
A comparison of self-supervised speech representations as input features for unsupervised acoustic word embeddings0
Discriminative Pre-training for Low Resource Title Compression in Conversational Grocery0
TF-CR: Weighting Embeddings for Text ClassificationCode0
Improving Zero Shot Learning Baselines with Commonsense Knowledge0
Cross-lingual Word Sense Disambiguation using mBERT Embeddings with Syntactic Dependencies0
A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings0
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity SearchCode0
SChME at SemEval-2020 Task 1: A Model Ensemble for Detecting Lexical Semantic ChangeCode0
A Computational Approach to Measuring the Semantic Divergence of Cognates0
Automatic Word Association Norms (AWAN)0
Towards Augmenting Lexical Resources for Slang and African American English0
Generating Varied Training Corpora in Runyankore Using a Combined Semantic and Syntactic, Pattern-Grammar-based Approach0
Amplifying the Range of News Stories with Creativity: Methods and their Evaluation, in Portuguese0
Combining financial word embeddings and knowledge-based features for financial text summarization UC3M-MC System at FNS-2020Code0
Neural Abstractive Multi-Document Summarization: Hierarchical or Flat Structure?0
Explaining the Trump Gap in Social Distancing Using COVID Discourse0
Leveraging Contextual Embeddings and Idiom Principle for Detecting Idiomaticity in Potentially Idiomatic Expressions0
Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages0
“Shakespeare in the Vectorian Age” – An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes0
Graph-based Syntactic Word Embeddings0
A Language-Based Approach to Fake News Detection Through Interpretable Features and BRNN0
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity0
Comparison between Voting Classifier and Deep Learning methods for Arabic Dialect Identification0
Demonstration of a Literature Based Discovery System based on Ontologies, Semantic Filters and Word Embeddings for the Raynaud Disease-Fish Oil Rediscovery0
MultiVitaminBooster at PARSEME Shared Task 2020: Combining Window- and Dependency-Based Features with Multilingual Contextualised Word Embeddings for VMWE Detection0
Interdependencies of Gender and Race in Contextualized Word Embeddings0
Argument from Old Man’s View: Assessing Social Bias in Argumentation0
CLaC at SMM4H 2020: Birth Defect Mention Detection0
Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings0
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing0
Unmasking Contextual Stereotypes: Measuring and Mitigating BERT’s Gender BiasCode1
Lexical Induction of Morphological and Orthographic Forms for Low-Resourced Languages0
Go Simple and Pre-Train on Domain-Specific Corpora: On the Role of Training Data for Text Classification0
Augmenting NLP models using Latent Feature Interpolations0
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 Information0
Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction0
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation0
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