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 1426–1450 of 4002 papers

TitleStatusHype
Neural Machine Translation from Historical Japanese to Contemporary Japanese Using Diachronically Domain-Adapted Word Embeddings—0
Composing Word Vectors for Japanese Compound Words Using Bilingual Word Embeddings—0
Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks—0
Interactive Re-Fitting as a Technique for Improving Word Embeddings—0
Multiple Word Embeddings for Increased Diversity of RepresentationCode0
Development of Word Embeddings for Uzbek Language—0
Leader: Prefixing a Length for Faster Word Vector SerializationCode0
Metaphor Detection using Deep Contextualized Word Embeddings—0
CogniFNN: A Fuzzy Neural Network Framework for Cognitive Word Embedding Evaluation—0
Visual-Semantic Embedding Model Informed by Structured Knowledge—0
Exploring the Linear Subspace Hypothesis in Gender Bias MitigationCode0
Word class flexibility: A deep contextualized approachCode0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment AnalysisCode0
Compositional and Lexical Semantics in RoBERTa, BERT and DistilBERT: A Case Study on CoQA—0
More Embeddings, Better Sequence Labelers?—0
Unsupervised Summarization by Jointly Extracting Sentences and Keywords—0
Lessons Learned from Applying off-the-shelf BERT: There is no Silver Bullet—0
ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile ApplicationsCode0
Coreference Resolution System for Indonesian Text with Mention Pair Method and Singleton Exclusion using Convolutional Neural NetworkCode0
Investigating Gender Bias in BERT—0
UPB at SemEval-2020 Task 9: Identifying Sentiment in Code-Mixed Social Media Texts using Transformers and Multi-Task Learning—0
Bio-inspired Structure Identification in Language Embeddings—0
Japanese Word Readability Assessment using Word Embeddings—0
VinAI at ChEMU 2020: An accurate system for named entity recognition in chemical reactions from patents—0
Discovering Bilingual Lexicons in Polyglot Word Embeddings—0
Show:102550
← PrevPage 58 of 161Next →

No leaderboard results yet.