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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 1651–1675 of 4002 papers

TitleStatusHype
LNMap: Departures from Isomorphic Assumption in Bilingual Lexicon Induction Through Non-Linear Mapping in Latent Space—0
On the Reliability of Test Collections for Evaluating Systems of Different Types—0
Intuitive Contrasting Map for Antonym EmbeddingsCode0
Combining Word Embeddings and N-grams for Unsupervised Document Summarization—0
When do Word Embeddings Accurately Reflect Surveys on our Beliefs About People?Code0
On Adversarial Examples for Biomedical NLP Tasks—0
Upgrading the Newsroom: An Automated Image Selection System for News Articles—0
Revisiting the Context Window for Cross-lingual Word Embeddings—0
Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets—0
A Study of Cross-Lingual Ability and Language-specific Information in Multilingual BERT—0
Effect of Text Color on Word Embeddings—0
A Hybrid Approach for Aspect-Based Sentiment Analysis Using Deep Contextual Word Embeddings and Hierarchical AttentionCode0
Too Many Claims to Fact-Check: Prioritizing Political Claims Based on Check-Worthiness—0
Exploring the Combination of Contextual Word Embeddings and Knowledge Graph Embeddings—0
Sentiment Analysis of Yelp Reviews: A Comparison of Techniques and ModelsCode0
Extending Text Informativeness Measures to Passage Interestingness Evaluation (Language Model vs. Word Embedding)—0
Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts—0
Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?—0
Improving Disfluency Detection by Self-Training a Self-Attentive Model—0
Word Equations: Inherently Interpretable Sparse Word Embeddingsthrough Sparse Coding—0
Decomposing Word Embedding with the Capsule Network—0
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation—0
Geometry-aware Domain Adaptation for Unsupervised Alignment of Word Embeddings—0
Analyzing autoencoder-based acoustic word embeddings—0
4chan & 8chan embeddings—0
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