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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 3601–3650 of 4002 papers

TitleStatusHype
Describing Images using Inferred Visual Dependency Representations—0
Designing a Russian Idiom-Annotated Corpus—0
Des pseudo-sens pour am\'eliorer l'extraction de synonymes \`a partir de plongements lexicaux (Pseudo-senses for improving the extraction of synonyms from word embeddings)—0
Des repr\'esentations continues de mots pour l'analyse d'opinions en arabe: une \'etude qualitative (Word embeddings for Arabic sentiment analysis : a qualitative study)—0
Detecting and Mitigating Indirect Stereotypes in Word Embeddings—0
Detecting Cross-Lingual Plagiarism Using Simulated Word Embeddings—0
Detecting Cybersecurity Events from Noisy Short Text—0
Detecting Fake News with Capsule Neural Networks—0
Detecting Figurative Word Occurrences Using Recurrent Neural Networks—0
Detecting Metaphorical Phrases in the Polish Language—0
Detecting Most Frequent Sense using Word Embeddings and BabelNet—0
Detecting Paraphrases of Standard Clause Titles in Insurance Contracts—0
Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings—0
Detecting Requirements Smells With Deep Learning: Experiences, Challenges and Future Work—0
Detecting Sarcasm Using Different Forms Of Incongruity—0
Detecting Semantically Equivalent Questions in Online User Forums—0
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling—0
Detecting Unseen Multiword Expressions in American Sign Language—0
Detecting weak and strong Islamophobic hate speech on social media—0
Detection of Adverse Drug Reaction in Tweets Using a Combination of Heterogeneous Word Embeddings—0
Detection of Multiword Expressions for Hindi Language using Word Embeddings and WordNet-based Features—0
Detect Toxic Content to Improve Online Conversations—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering—0
Developing Conversational Data and Detection of Conversational Humor in Telugu—0
Development of a Japanese Personality Dictionary based on Psychological Methods—0
Development of Word Embeddings for Uzbek Language—0
DFKI-MLT System Description for the WMT18 Automatic Post-editing Task—0
D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities—0
D-Graph: AI-Assisted Design Concept Exploration Graph—0
Diachronic degradation of language models: Insights from social media—0
Diachronic Embeddings for People in the News—0
Diachronic Sense Modeling with Deep Contextualized Word Embeddings: An Ecological View—0
Diachronic word embeddings and semantic shifts: a survey—0
Dialectograms: Machine Learning Differences between Discursive Communities—0
Dialects Identification of Armenian Language—0
Dialog State Tracking: A Neural Reading Comprehension Approach—0
Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network—0
Dialogue Session Segmentation by Embedding-Enhanced TextTiling—0
Dialogue Term Extraction using Transfer Learning and Topological Data Analysis—0
DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT Embeddings—0
DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features—0
Different Contexts Lead to Different Word Embeddings—0
Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe—0
Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe—0
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder—0
Differential Privacy and Natural Language Processing to Generate Contextually Similar Decoy Messages in Honey Encryption Scheme—0
Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models—0
Di-LSTM Contrast : A Deep Neural Network for Metaphor Detection—0
Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings—0
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