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 3526–3550 of 4002 papers

TitleStatusHype
On the Dimensionality of Word EmbeddingCode0
Enhancing Deep Learning with Embedded Features for Arabic Named Entity RecognitionCode0
On the Downstream Performance of Compressed Word EmbeddingsCode0
Classifying Relations by Ranking with Convolutional Neural NetworksCode0
Learning language through picturesCode0
Learning language variations in news corpora through differential embeddingsCode0
Learning Lexical Subspaces in a Distributional Vector SpaceCode0
Learning Meta-Embeddings by Using Ensembles of Embedding SetsCode0
Semantic Structure and Interpretability of Word EmbeddingsCode0
On the Effect of Low-Frequency Terms on Neural-IR ModelsCode0
SemSup: Semantic Supervision for Simple and Scalable Zero-shot GeneralizationCode0
VAST: The Valence-Assessing Semantics Test for Contextualizing Language ModelsCode0
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric ApproachCode0
Enhancing Word Embeddings with Knowledge Extracted from Lexical ResourcesCode0
Transformers without Tears: Improving the Normalization of Self-AttentionCode0
SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word EmbeddingsCode0
A Survey on Sentence Embedding Models Performance for Patent AnalysisCode0
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word EmbeddingsCode0
Enriching Word Embeddings with Temporal and Spatial InformationCode0
Enriching Word Vectors with Subword InformationCode0
An Open-World Extension to Knowledge Graph Completion ModelsCode0
VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition ModelingCode0
Learning Neural Word Salience ScoresCode0
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based ApproachCode0
Better Summarization Evaluation with Word Embeddings for ROUGECode0
Show:102550
← PrevPage 142 of 161Next →

No leaderboard results yet.