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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 751–800 of 4002 papers

TitleStatusHype
Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor DetectionCode0
Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist NewspapersCode0
Inducing a Lexicon of Abusive Words – a Feature-Based ApproachCode0
CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing SignalsCode0
Detecting Anxiety through RedditCode0
CogniVal: A Framework for Cognitive Word Embedding EvaluationCode0
Diachronic Word Embeddings Reveal Statistical Laws of Semantic ChangeCode0
Specializing Unsupervised Pretraining Models for Word-Level Semantic SimilarityCode0
A Semi-supervised Framework for Image CaptioningCode0
Insights into Analogy Completion from the Biomedical DomainCode0
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content MeasurementCode0
Collapsed Language Models Promote FairnessCode0
Collocation Classification with Unsupervised Relation VectorsCode0
Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short TextsCode0
Inter and Intra Topic Structure Learning with Word EmbeddingsCode0
Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgroupingCode0
Effective Dimensionality Reduction for Word EmbeddingsCode0
Evaluating Biased Attitude Associations of Language Models in an Intersectional ContextCode0
Izindaba-Tindzaba: Machine learning news categorisation for Long and Short Text for isiZulu and SiswatiCode0
Joint Multiclass Debiasing of Word EmbeddingsCode0
Combining financial word embeddings and knowledge-based features for financial text summarization UC3M-MC System at FNS-2020Code0
A Simple and Effective Approach for Fine Tuning Pre-trained Word Embeddings for Improved Text ClassificationCode0
Degree-Aware Alignment for Entities in TailCode0
DefSent+: Improving sentence embeddings of language models by projecting definition sentences into a quasi-isotropic or isotropic vector space of unlimited dictionary entriesCode0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment AnalysisCode0
Definition Frames: Using Definitions for Hybrid Concept RepresentationsCode0
Combining Representations For Effective Citation ClassificationCode0
A Simple Approach to Learn Polysemous Word EmbeddingsCode0
Definition Modeling: Learning to define word embeddings in natural languageCode0
Density Matching for Bilingual Word EmbeddingCode0
Bidirectional LSTM-CRF for Clinical Concept ExtractionCode0
Language Models with Pre-Trained (GloVe) Word EmbeddingsCode0
Bidirectional LSTM-CRF for Clinical Concept ExtractionCode0
Combining Word Embeddings and Feature Embeddings for Fine-grained Relation ExtractionCode0
Learning Composition Models for Phrase EmbeddingsCode0
Deep word embeddings for visual speech recognitionCode0
Learning Diachronic Analogies to Analyze Concept ChangeCode0
Deep Text Mining of Instagram Data Without Strong SupervisionCode0
Common Sense Bias in Semantic Role LabelingCode0
Learning Dynamic Contextualised Word Embeddings via Template-based Temporal AdaptationCode0
Learning language through picturesCode0
Comparative Analysis of Word Embeddings for Capturing Word SimilaritiesCode0
Bidirectional Attention as a Mixture of Continuous Word ExpertsCode0
Deep Unordered Composition Rivals Syntactic Methods for Text ClassificationCode0
Def2Vec: Extensible Word Embeddings from Dictionary DefinitionsCode0
Learning Neural Word Salience ScoresCode0
Learning Personal Food Preferences via Food Logs EmbeddingCode0
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and DocumentsCode0
Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRFCode0
Deep Pivot-Based Modeling for Cross-language Cross-domain Transfer with Minimal GuidanceCode0
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