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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 926–950 of 4002 papers

TitleStatusHype
Lasige-BioTM at ProfNER: BiLSTM-CRF and contextual Spanish embeddings for Named Entity Recognition and Tweet Binary Classification—0
Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media—0
Word Embeddings, Cosine Similarity and Deep Learning for Identification of Professions & Occupations in Health-related Social Media—0
Fine-tuning BERT to classify COVID19 tweets containing symptoms—0
Exploration des relations sémantiques sous-jacentes aux plongements contextuels de mots (Exploring semantic relations underlying contextual word embeddings)—0
Measuring Biases of Word Embeddings: What Similarity Measures and Descriptive Statistics to Use?—0
The Effect of Pretraining on Extractive Summarization for Scientific Documents—0
Profiling of Intertextuality in Latin Literature Using Word EmbeddingsCode0
Query2Prod2Vec: Grounded Word Embeddings for eCommerceCode1
Cross-Lingual Word Embedding Refinement by _1 Norm OptimisationCode1
Morphology-Aware Meta-Embeddings for TamilCode0
Field Embedding: A Unified Grain-Based Framework for Word Representation—0
Data Filtering using Cross-Lingual Word Embeddings—0
LenAtten: An Effective Length Controlling Unit For Text SummarizationCode0
Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives—0
SA2SL: From Aspect-Based Sentiment Analysis to Social Listening System for Business IntelligenceCode1
An Explanatory Query-Based Framework for Exploring Academic Expertise—0
Semantic Frame Induction using Masked Word Embeddings and Two-Step Clustering—0
RAW-C: Relatedness of Ambiguous Words--in Context (A New Lexical Resource for English)Code0
Inspecting the concept knowledge graph encoded by modern language models—0
A data-driven strategy to combine word embeddings in information retrieval—0
Word Embedding Transformation for Robust Unsupervised Bilingual Lexicon Induction—0
HIN-RNN: A Graph Representation Learning Neural Network for Fraudster Group Detection With No Handcrafted Features—0
ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents—0
View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data—0
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