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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 1326–1350 of 4002 papers

TitleStatusHype
Neural Machine Translation from Historical Japanese to Contemporary Japanese Using Diachronically Domain-Adapted Word Embeddings—0
Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks—0
"Did you really mean what you said?" : Sarcasm Detection in Hindi-English Code-Mixed Data using Bilingual Word EmbeddingsCode1
Multiple Word Embeddings for Increased Diversity of RepresentationCode0
Interactive Re-Fitting as a Technique for Improving Word Embeddings—0
Development of Word Embeddings for Uzbek Language—0
BERT for Monolingual and Cross-Lingual Reverse DictionaryCode1
Leader: Prefixing a Length for Faster Word Vector SerializationCode0
Multi-Relational Embedding for Knowledge Graph Representation and AnalysisCode1
Metaphor Detection using Deep Contextualized Word Embeddings—0
iNLTK: Natural Language Toolkit for Indic LanguagesCode1
CogniFNN: A Fuzzy Neural Network Framework for Cognitive Word Embedding Evaluation—0
Latin BERT: A Contextual Language Model for Classical PhilologyCode1
Visual-Semantic Embedding Model Informed by Structured Knowledge—0
Modality-Transferable Emotion Embeddings for Low-Resource Multimodal Emotion RecognitionCode1
Vector Projection Network for Few-shot Slot Tagging in Natural Language UnderstandingCode1
Exploring the Linear Subspace Hypothesis in Gender Bias MitigationCode0
Dual-path CNN with Max Gated block for Text-Based Person Re-identificationCode1
Word class flexibility: A deep contextualized approachCode0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment AnalysisCode0
Compositional and Lexical Semantics in RoBERTa, BERT and DistilBERT: A Case Study on CoQA—0
More Embeddings, Better Sequence Labelers?—0
Unsupervised Summarization by Jointly Extracting Sentences and Keywords—0
Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item AnnotationCode1
Lessons Learned from Applying off-the-shelf BERT: There is no Silver Bullet—0
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