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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 701–725 of 4002 papers

TitleStatusHype
Chemical Identification and Indexing in PubMed Articles via BERT and Text-to-Text Approaches—0
Chinese Embedding via Stroke and Glyph Information: A Dual-channel View—0
Bootstrap Domain-Specific Sentiment Classifiers from Unlabeled Corpora—0
Chinese Hypernym-Hyponym Extraction from User Generated Categories—0
Chinese Zero Pronoun Resolution with Deep Neural Networks—0
Are Girls Neko or Sh\=ojo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization—0
Acoustic Word Embedding System for Code-Switching Query-by-example Spoken Term Detection—0
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research—0
CitiusNLP at SemEval-2020 Task 3: Comparing Two Approaches for Word Vector Contextualization—0
City2City: Translating Place Representations across Cities—0
Boosting Named Entity Recognition with Neural Character Embeddings—0
CLaC at SMM4H 2020: Birth Defect Mention Detection—0
CLaC Lab at SemEval-2019 Task 3: Contextual Emotion Detection Using a Combination of Neural Networks and SVM—0
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings—0
An Unsupervised Approach for Mapping between Vector Spaces—0
A Review of Cross-Domain Text-to-SQL Models—0
Classification Attention for Chinese NER—0
Coming to its senses: Lessons learned from Approximating Retrofitted BERT representations for Word Sense information—0
A Review of Standard Text Classification Practices for Multi-label Toxicity Identification of Online Content—0
Classification of Micro-Texts Using Sub-Word Embeddings—0
Classifying Out-of-vocabulary Terms in a Domain-Specific Social Media Corpus—0
A Review on Deep Learning Techniques Applied to Answer Selection—0
Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention—0
Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings—0
Community Evaluation and Exchange of Word Vectors at wordvectors.org—0
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