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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 3451–3500 of 4002 papers

TitleStatusHype
A Systematic Comparison of English Noun Compound RepresentationsCode0
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse TargetsCode0
Learning and Evaluating Character Representations in NovelsCode0
Object Priors for Classifying and Localizing Unseen ActionsCode0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data SetCode0
Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error StatesCode0
Efficient Vector Representation for Documents through CorruptionCode0
EF-Net: A Deep Learning Approach Combining Word Embeddings and Feature Fusion for Patient Disposition AnalysisCode0
A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic ChangeCode0
EigenSent: Spectral sentence embeddings using higher-order Dynamic Mode DecompositionCode0
Eliciting Explicit Knowledge From Domain Experts in Direct Intrinsic Evaluation of Word Embeddings for Specialized DomainsCode0
Global Textual Relation Embedding for Relational UnderstandingCode0
Asynchronous Training of Word Embeddings for Large Text CorporaCode0
Beyond One-Hot-Encoding: Injecting Semantics to Drive Image ClassifiersCode0
Unsupervised Open Relation ExtractionCode0
Unsupervised Parallel Sentence Extraction with Parallel Segment Detection Helps Machine TranslationCode0
Interpretable Segmentation of Medical Free-Text Records Based on Word EmbeddingsCode0
Clustering-Based Article Identification in Historical NewspapersCode0
InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme ClassificationCode0
Training Cross-Lingual embeddings for Setswana and SepediCode0
On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual LearningCode0
Embeddings Evaluation Using a Novel Measure of Semantic SimilarityCode0
Training Temporal Word Embeddings with a CompassCode0
Embeddings for Word Sense Disambiguation: An Evaluation StudyCode0
On Dimensional Linguistic Properties of the Word Embedding SpaceCode0
ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over CenturiesCode0
Embedding Strategies for Specialized Domains: Application to Clinical Entity RecognitionCode0
One of these words is not like the other: a reproduction of outlier identification using non-contextual word representationsCode0
Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient MobilityCode0
A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding SpacesCode0
CLIP-Decoder : ZeroShot Multilabel Classification using Multimodal CLIP Aligned RepresentationCode0
Learning Composition Models for Phrase EmbeddingsCode0
Task-oriented Word Embedding for Text ClassificationCode0
A Comparative Analysis of Static Word Embeddings for HungarianCode0
Beyond Film Subtitles: Is YouTube the Best Approximation of Spoken Vocabulary?Code0
emoji2vec: Learning Emoji Representations from their DescriptionCode0
Learning Contextual Tag Embeddings for Cross-Modal Alignment of Audio and TagsCode0
One-to-X analogical reasoning on word embeddings: a case for diachronic armed conflict prediction from news textsCode0
EmoSense at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual ConversationsCode0
Semantic Properties of cosine based bias scores for word embeddingsCode0
Clinical Flair: A Pre-Trained Language Model for Spanish Clinical Natural Language ProcessingCode0
One Word, Two Sides: Traces of Stance in Contextualized Word RepresentationsCode0
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity SearchCode0
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical DataCode0
1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential PrivacyCode0
Learning Crosslingual Word Embeddings without Bilingual CorporaCode0
Learning Diachronic Analogies to Analyze Concept ChangeCode0
Audio Caption in a Car Setting with a Sentence-Level LossCode0
Better Word Embeddings by Disentangling Contextual n-Gram InformationCode0
Word-Class Embeddings for Multiclass Text ClassificationCode0
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