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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 901–925 of 4002 papers

TitleStatusHype
A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution.Code0
Predicting Concreteness and Imageability of Words Within and Across Languages via Word EmbeddingsCode0
Better Word Embeddings by Disentangling Contextual n-Gram InformationCode0
Pretrained Transformers for Simple Question Answering over Knowledge GraphsCode0
Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention SelectionCode0
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to ModelingCode0
Attentive Mimicking: Better Word Embeddings by Attending to Informative ContextsCode0
Dictionary-based Debiasing of Pre-trained Word EmbeddingsCode0
Attentive Neural Network for Named Entity Recognition in VietnameseCode0
Probing for Semantic Classes: Diagnosing the Meaning Content of Word EmbeddingsCode0
Correlations between Word Vector SetsCode0
CoSimLex: A Resource for Evaluating Graded Word Similarity in ContextCode0
Better Summarization Evaluation with Word Embeddings for ROUGECode0
Putting words in context: LSTM language models and lexical ambiguityCode0
Quantifying Lexical Semantic Shift via Unbalanced Optimal TransportCode0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment AnalysisCode0
Density Matching for Bilingual Word EmbeddingCode0
DefSent+: Improving sentence embeddings of language models by projecting definition sentences into a quasi-isotropic or isotropic vector space of unlimited dictionary entriesCode0
A Bi-Encoder LSTM Model For Learning Unstructured DialogsCode0
Query Focused Multi-document Summarisation of Biomedical Texts: Macquarie Universiy and the Australian National University at BioASQ8bCode0
Cross-domain Semantic Parsing via ParaphrasingCode0
A Latent Variable Model Approach to PMI-based Word EmbeddingsCode0
Degree-Aware Alignment for Entities in TailCode0
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
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and DocumentsCode0
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