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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 1926–1950 of 4002 papers

TitleStatusHype
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 EmbeddingsCode0
It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution—0
Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space—0
Political Stance in DanishCode0
Cross-Lingual Word Embeddings for Morphologically Rich Languages—0
Unsupervised Inference of Object Affordance from Text Corpora—0
Multilingual Complex Word Identification: Convolutional Neural Networks with Morphological and Linguistic Features—0
Sparse Victory -- A Large Scale Systematic Comparison of count-based and prediction-based vectorizers for text classificationCode0
Toward Multilingual Identification of Online Registers—0
A study of semantic augmentation of word embeddings for extractive summarization—0
Comparing the Performance of Feature Representations for the Categorization of the Easy-to-Read Variety vs Standard Language—0
A Classification-Based Approach to Cognate Detection Combining Orthographic and Semantic Similarity Information—0
Speculation and Negation detection in French biomedical corpora—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Evaluation of Stacked Embeddings for Bulgarian on the Downstream Tasks POS and NERC—0
Classification of Micro-Texts Using Sub-Word Embeddings—0
Whom to Learn From? Graph- vs. Text-based Word Embeddings—0
Evaluating the Consistency of Word Embeddings from Small Data—0
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations—0
Tweaks and Tricks for Word Embedding Disruptions—0
SenZi: A Sentiment Analysis Lexicon for the Latinised Arabic (Arabizi)—0
Towards High Accuracy Named Entity Recognition for Icelandic—0
An Improved Neural Baseline for Temporal Relation Extraction—0
Named-Entity Recognition for NorwegianCode0
Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-TrainingCode0
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