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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 651–675 of 4002 papers

TitleStatusHype
Knowing Where and What: Unified Word Block Pretraining for Document UnderstandingCode0
SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation—0
Exploring Wasserstein Distance across Concept Embeddings for Ontology Matching—0
A Context-Sensitive Word Embedding Approach for The Detection of Troll Tweets—0
Stroke-Based Autoencoders: Self-Supervised Learners for Efficient Zero-Shot Chinese Character Recognition—0
A methodology to characterize bias and harmful stereotypes in natural language processing in Latin AmericaCode0
Myers-Briggs personality classification from social media text using pre-trained language models—0
A Comparative Study on Word Embeddings and Social NLP TasksCode0
Clinical Flair: A Pre-Trained Language Model for Spanish Clinical Natural Language ProcessingCode0
Cross-Language Transfer of High-Quality Annotations: Combining Neural Machine Translation with Cross-Linguistic Span Alignment to Apply NER to Clinical Texts in a Low-Resource LanguageCode0
Analysis of Gender Bias in Social Perception and Judgement Using Chinese Word Embeddings—0
When Polysemy Matters: Modeling Semantic Categorization with Word Embeddings—0
TLDR at SemEval-2022 Task 1: Using Transformers to Learn Dictionaries and Representations—0
Plumeria at SemEval-2022 Task 6: Sarcasm Detection for English and Arabic Using Transformers and Data Augmentation—0
Unsupervised Mitigating Gender Bias by Character Components: A Case Study of Chinese Word Embedding—0
Interpreting Emoji with Emoji—0
Language Models for Code-switch Detection of te reo Māori and English in a Low-resource Setting—0
Indigenous Language Revitalization and the Dilemma of Gender Bias—0
TurkishDelightNLP: A Neural Turkish NLP ToolkitCode0
BL.Research at SemEval-2022 Task 1: Deep networks for Reverse Dictionary using embeddings and LSTM autoencodersCode0
Team Stanford ACMLab at SemEval 2022 Task 4: Textual Analysis of PCL Using Contextual Word Embeddings—0
LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover’s Distance—0
Edinburgh at SemEval-2022 Task 1: Jointly Fishing for Word Embeddings and DefinitionsCode0
Subword-based Cross-lingual Transfer of Embeddings from Hindi to Marathi and Nepali—0
Raccoons at SemEval-2022 Task 11: Leveraging Concatenated Word Embeddings for Named Entity Recognition—0
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