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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 1201–1225 of 4002 papers

TitleStatusHype
Decoding Brain Activity Associated with Literal and Metaphoric Sentence Comprehension Using Distributional Semantic Models—0
Automatic Noun Compound Interpretation using Deep Neural Networks and Word Embeddings—0
Deceptive Opinion Spam Detection Using Neural Network—0
Metaphor Interpretation Using Word Embeddings—0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
Automatic Learning of Modality Exclusivity Norms with Crosslingual Word Embeddings—0
Debiasing Pretrained Text Encoders by Paying Attention to Paying Attention—0
Automatic Labeling of Problem-Solving Dialogues for Computational Microgenetic Learning Analytics—0
Automatic Generation of Multiple-Choice Questions—0
Debiasing Embeddings for Reduced Gender Bias in Text Classification—0
An efficient domain-independent approach for supervised keyphrase extraction and ranking—0
Adversarial Training for Unsupervised Bilingual Lexicon Induction—0
A Comparison of Context-sensitive Models for Lexical Substitution—0
A Bayesian approach to uncertainty in word embedding bias estimation—0
DCU: Using Distributional Semantics and Domain Adaptation for the Semantic Textual Similarity SemEval-2015 Task 2—0
DCC-Uchile at SemEval-2020 Task 1: Temporal Referencing Word Embeddings—0
DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison—0
Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia—0
An Efficient Cross-lingual Model for Sentence Classification Using Convolutional Neural Network—0
Data Sets: Word Embeddings Learned from Tweets and General Data—0
Automatic Creation of Correspondence Table of Meaning Tags from Two Dictionaries in One Language Using Bilingual Word Embedding—0
Data Filtering using Cross-Lingual Word Embeddings—0
Automatic Community Creation for Abstractive Spoken Conversations Summarization—0
Anchor-based Bilingual Word Embeddings for Low-Resource Languages—0
Data-Driven Mitigation of Adversarial Text Perturbation—0
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