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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 2276–2300 of 4002 papers

TitleStatusHype
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling—0
SparseGAN: Sparse Generative Adversarial Network for Text Generation—0
SParse: Ko University Graph-Based Parsing System for the CoNLL 2018 Shared Task—0
Sparsifying Word Representations for Deep Unordered Sentence Modeling—0
Spatio-temporal Sign Language Representation and Translation—0
Speak2Sign3D: A Multi-modal Pipeline for English Speech to American Sign Language Animation—0
Specializing Word Embeddings for Similarity or Relatedness—0
Speculation and Negation detection in French biomedical corpora—0
Splitting Compounds by Semantic Analogy—0
Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources—0
Spying on your neighbors: Fine-grained probing of contextual embeddings for information about surrounding words—0
SSNCSE_NLP@LT-EDI-ACL2022: Homophobia/Transphobia Detection in Multiple Languages using SVM Classifiers and BERT-based Transformers—0
Stacking with Auxiliary Features for Visual Question Answering—0
Stance and Sentiment in Tweets—0
Stance Classification, Outcome Prediction, and Impact Assessment: NLP Tasks for Studying Group Decision-Making—0
Stance Detection in Fake News A Combined Feature Representation—0
Stance Detection with BERT Embeddings for Credibility Analysis of Information on Social Media—0
Stanford MLab at SemEval-2021 Task 1: Tree-Based Modelling of Lexical Complexity using Word Embeddings—0
Static Word Embeddings for Sentence Semantic Representation—0
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound—0
Statistically significant detection of semantic shifts using contextual word embeddings—0
sthruggle at SemEval-2019 Task 5: An Ensemble Approach to Hate Speech Detection—0
Story Cloze Ending Selection Baselines and Data Examination—0
Streaming word similarity mining on the cheap—0
Stroke-Based Autoencoders: Self-Supervised Learners for Efficient Zero-Shot Chinese Character Recognition—0
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