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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 1101–1125 of 4002 papers

TitleStatusHype
Gender bias in (non)-contextual clinical word embeddings for stereotypical medical categories—0
Angular-Based Word Meta-Embedding Learning—0
BhamNLP at SemEval-2020 Task 12: An Ensemble of Different Word Embeddings and Emotion Transfer Learning for Arabic Offensive Language Identification in Social Media—0
Beyond Word Embeddings: Learning Entity and Concept Representations from Large Scale Knowledge Bases—0
An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining—0
A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models—0
Distinguishing Japanese Non-standard Usages from Standard Ones—0
Distilling Word Embeddings: An Encoding Approach—0
Distributed Prediction of Relations for Entities: The Easy, The Difficult, and The Impossible—0
A bilingual approach to specialised adjectives through word embeddings in the karstology domain—0
Diachronic Embeddings for People in the News—0
An Exploratory Analysis on the Explanatory Potential of Embedding-Based Measures of Semantic Transparency for Malay Word Recognition—0
Distilled embedding: non-linear embedding factorization using knowledge distillation—0
Distributed Representations for Unsupervised Semantic Role Labeling—0
Distributed Vector Representations for Unsupervised Automatic Short Answer Grading—0
Distributional Lesk: Effective Knowledge-Based Word Sense Disambiguation—0
Diachronic degradation of language models: Insights from social media—0
Beyond Offline Mapping: Learning Cross-lingual Word Embeddings through Context Anchoring—0
An Exploration of Word Embedding Initialization in Deep-Learning Tasks—0
Diachronic Sense Modeling with Deep Contextualized Word Embeddings: An Ecological View—0
Diachronic word embeddings and semantic shifts: a survey—0
A General Framework for Detecting Metaphorical Collocations—0
An Exploratory Study on Temporally Evolving Discussion around Covid-19 using Diachronic Word Embeddings—0
Distilled Wasserstein Learning for Word Embedding and Topic Modeling—0
D-Graph: AI-Assisted Design Concept Exploration Graph—0
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