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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 2201–2225 of 4002 papers

TitleStatusHype
Evaluation of Question Answering Systems: Complexity of judging a natural language—0
Evaluation of Stacked Embeddings for Bulgarian on the Downstream Tasks POS and NERC—0
Evaluation of Taxonomy Enrichment on Diachronic WordNet Versions—0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
Evaluation of Word Embeddings for the Social Sciences—0
Event Detection Using Frame-Semantic Parser—0
Event extraction from Twitter using Non-Parametric Bayesian Mixture Model with Word Embeddings—0
Event Ordering with a Generalized Model for Sieve Prediction Ranking—0
Event Prominence Extraction Combining a Knowledge-Based Syntactic Parser and a BERT Classifier for Dutch—0
Event Role Extraction using Domain-Relevant Word Representations—0
Event Role Labelling using a Neural Network Model (\'Etiquetage en r\^oles \'ev\'enementiels fond\'e sur l'utilisation d'un mod\`ele neuronal) [in French]—0
Evolving Hate Speech Online: An Adaptive Framework for Detection and Mitigation—0
Evolving Large Text Corpora: Four Versions of the Icelandic Gigaword Corpus—0
Exact gradient updates in time independent of output size for the spherical loss family—0
Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework—0
Example-based Acquisition of Fine-grained Collocation Resources—0
ExB Themis: Extensive Feature Extraction from Word Alignments for Semantic Textual Similarity—0
Expanding Subjective Lexicons for Social Media Mining with Embedding Subspaces—0
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings—0
Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity—0
Experimental Evaluation of Deep Learning models for Marathi Text Classification—0
Experiments on a Guarani Corpus of News and Social Media—0
Explainability of Text Processing and Retrieval Methods: A Critical Survey—0
Explainable Identification of Hate Speech towards Islam using Graph Neural Networks—0
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning—0
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