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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 1676–1700 of 4002 papers

TitleStatusHype
Adversarial Transfer Learning for Punctuation Restoration—0
DSTC8-AVSD: Multimodal Semantic Transformer Network with Retrieval Style Word Generator—0
Give your Text Representation Models some Love: the Case for BasqueCode0
Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n^6) down to O(n^3)Code0
A Novel Method of Extracting Topological Features from Word Embeddings—0
Topological Data Analysis in Text Classification: Extracting Features with Additive Information—0
Data-driven models and computational tools for neurolinguistics: a language technology perspectiveCode0
Temporal Embeddings and Transformer Models for Narrative Text Understanding—0
Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá—0
A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic—0
Leveraging Foreign Language Labeled Data for Aspect-Based Opinion Mining—0
Text Similarity Using Word Embeddings to Classify Misinformation—0
Word Sense Disambiguation for 158 Languages using Word Embeddings Only—0
Using word embeddings to improve the discriminability of co-occurrence text networks—0
A Precisely Xtreme-Multi Channel Hybrid Approach For Roman Urdu Sentiment Analysis—0
Text classification with word embedding regularization and soft similarity measureCode0
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity—0
Combining Pretrained High-Resource Embeddings and Subword Representations for Low-Resource Languages—0
Joint Multiclass Debiasing of Word EmbeddingsCode0
Discovering linguistic (ir)regularities in word embeddings through max-margin separating hyperplanes—0
Quality of Word Embeddings on Sentiment Analysis Tasks—0
Captioning Images with Novel Objects via Online Vocabulary Expansion—0
Brazilian Lyrics-Based Music Genre Classification Using a BLSTM Network—0
Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach—0
Toward Interpretability of Dual-Encoder Models for Dialogue Response Suggestions—0
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