SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3251–3275 of 4002 papers

TitleStatusHype
A Multidimensional Lexicon for Interpersonal Stancetaking—0
Neural Joint Model for Transition-based Chinese Syntactic Analysis—0
An Unsupervised Neural Attention Model for Aspect ExtractionCode0
Apples to Apples: Learning Semantics of Common Entities Through a Novel Comprehension Task—0
A Progressive Learning Approach to Chinese SRL Using Heterogeneous Data—0
Skip-Gram − Zipf + Uniform = Vector Additivity—0
Zara Returns: Improved Personality Induction and Adaptation by an Empathetic Virtual Agent—0
Learning bilingual word embeddings with (almost) no bilingual data—0
Varying Linguistic Purposes of Emoji in (Twitter) Context—0
Bilingual Word Embeddings with Bucketed CNN for Parallel Sentence Extraction—0
Multi-Attention Network for One Shot Learning—0
Obtaining referential word meanings from visual and distributional information: Experiments on object naming—0
Character-Aware Neural Morphological Disambiguation—0
Exploring Neural Text Simplification ModelsCode0
Exploring Diachronic Lexical Semantics with JeSemECode0
Methodical Evaluation of Arabic Word Embeddings—0
ESTEEM: A Novel Framework for Qualitatively Evaluating and Visualizing Spatiotemporal Embeddings in Social MediaCode0
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word EmbeddingsCode0
Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts—0
Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering—0
Discretely Coding Semantic Rank Orders for Supervised Image Hashing—0
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognitionCode0
Neural Question Answering at BioASQ 5B—0
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context—0
Jointly Learning Word Embeddings and Latent Topics—0
Show:102550
← PrevPage 131 of 161Next →

No leaderboard results yet.