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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 1401–1425 of 4002 papers

TitleStatusHype
Evaluating Metrics for Bias in Word Embeddings—0
Evaluating Monolingual and Crosslingual Embeddings on Datasets of Word Association Norms—0
Chemical Identification and Indexing in PubMed Articles via BERT and Text-to-Text Approaches—0
Evaluating multi-sense embeddings for semantic resolution monolingually and in word translation—0
Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks—0
Chinese Embedding via Stroke and Glyph Information: A Dual-channel View—0
Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings—0
Detecting Paraphrases of Standard Clause Titles in Insurance Contracts—0
Chinese Hypernym-Hyponym Extraction from User Generated Categories—0
Chinese Event Extraction Using DeepNeural Network with Word Embedding—0
Chinese Zero Pronoun Resolution with Deep Neural Networks—0
Evaluating Sub-word Embeddings in Cross-lingual Models—0
Evaluating the Consistency of Word Embeddings from Small Data—0
Evaluating the Impact of Sub-word Information and Cross-lingual Word Embeddings on Mi'kmaq Language Modelling—0
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification—0
Evaluating the timing and magnitude of semantic change in diachronic word embedding models—0
Detecting Most Frequent Sense using Word Embeddings and BabelNet—0
Evaluating the Underlying Gender Bias in Contextualized Word Embeddings—0
Evaluating vector-space models of analogy—0
Evaluating Word Embedding Hyper-Parameters for Similarity and Analogy Tasks—0
Evaluating Word Embedding Models: Methods and Experimental Results—0
Evaluating Word Embeddings for Indonesian--English Code-Mixed Text Based on Synthetic Data—0
Detecting Metaphorical Phrases in the Polish Language—0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts—0
Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings—0
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