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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 2851–2900 of 4002 papers

TitleStatusHype
Measuring and Modeling Language Change—0
Measuring a Texts Fairness Dimensions Using Machine Learning Based on Social Psychological Factors—0
Measuring Biases of Word Embeddings: What Similarity Measures and Descriptive Statistics to Use?—0
Measuring Diachronic Evolution of Evaluative Adjectives with Word Embeddings: the Case for English, Norwegian, and Russian—0
Measuring Issue Ownership using Word Embeddings—0
Measuring Similarity by Linguistic Features rather than Frequency—0
Measuring Social Bias in Knowledge Graph Embeddings—0
Measuring Topic Coherence through Optimal Word Buckets—0
Medical Word Embeddings for Spanish: Development and Evaluation—0
Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings—0
Membership Inference on Word Embedding and Beyond—0
Merging Verb Senses of Hindi WordNet using Word Embeddings—0
Meta-Embeddings for Natural Language Inference and Semantic Similarity tasks—0
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German—0
Metaphor Detection in a Poetry Corpus—0
Metaphor Detection Using Contextual Word Embeddings From Transformers—0
Metaphor Detection using Deep Contextualized Word Embeddings—0
Methodical Evaluation of Arabic Word Embeddings—0
Methods for Numeracy-Preserving Word Embeddings—0
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification—0
microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF—0
MineriaUNAM at SemEval-2020 Task 3: Predicting Contextual WordSimilarity Using a Centroid Based Approach and Word Embeddings—0
Minimally-Supervised Relation Induction from Pre-trained Language Model—0
Minimally-Supervised Relation Induction from Pre-trained Language Model—0
Mining Semantic Relations from Comparable Corpora through Intersections of Word Embeddings—0
Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings—0
Misspelling Correction with Pre-trained Contextual Language Model—0
Mitigating Gender Bias in Contextual Word Embeddings—0
Mitigating Political Bias in Language Models Through Reinforced Calibration—0
MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network—0
MITRE: Seven Systems for Semantic Similarity in Tweets—0
Mixed Membership Word Embeddings for Computational Social Science—0
Mixing syntagmatic and paradigmatic information for concept detection—0
Mixtures of Deep Neural Experts for Automated Speech Scoring—0
Model-based Word Embeddings from Decompositions of Count Matrices—0
Model Choices Influence Attributive Word Associations: A Semi-supervised Analysis of Static Word Embeddings—0
Model-Free Context-Aware Word Composition—0
Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding—0
Modeling Noisiness to Recognize Named Entities using Multitask Neural Networks on Social Media—0
Modeling Order in Neural Word Embeddings at Scale—0
Modeling Personal Biases in Language Use by Inducing Personalized Word Embeddings—0
Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach—0
Modeling Tension in Stories via Commonsense Reasoning and Emotional Word Embeddings—0
Modeling Text using the Continuous Space Topic Model with Pre-Trained Word Embeddings—0
Modeling the Non-Substitutability of Multiword Expressions with Distributional Semantics and a Log-Linear Model—0
Modeling with Recurrent Neural Networks for Open Vocabulary Slots—0
Modelling metaphor with attribute-based semantics—0
Modelling Multi-modal Cross-interaction for ML-FSIC Based on Local Feature Selection—0
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks—0
Modelling Representation Noise in Emotion Analysis using Gaussian Processes—0
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