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 2426–2450 of 4002 papers

TitleStatusHype
A Framework for Understanding the Role of Morphology in Universal Dependency Parsing—0
Unsupervised Bilingual Lexicon Induction via Latent Variable Models—0
CEA LIST: Processing Low-Resource Languages for CoNLL 2018Code0
Self-Governing Neural Networks for On-Device Short Text ClassificationCode0
Joint Learning for Targeted Sentiment Analysis—0
Learning Representations for Detecting Abusive Language—0
IRISA at SMM4H 2018: Neural Network and Bagging for Tweet Classification—0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Unsupervised Parallel Sentence Extraction from Comparable Corpora—0
Self-training improves Recurrent Neural Networks performance for Temporal Relation Extraction—0
Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data—0
Learning Text Representations for 500K Classification Tasks on Named Entity DisambiguationCode0
Learning Unsupervised Word Translations Without Adversaries—0
InferLite: Simple Universal Sentence Representations from Natural Language Inference Data—0
In-domain Context-aware Token Embeddings Improve Biomedical Named Entity Recognition—0
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings—0
Refining Pretrained Word Embeddings Using Layer-wise Relevance Propagation—0
Word Embeddings for Code-Mixed Language Processing—0
A Morphology-Based Representation Model for LSTM-Based Dependency Parsing of Agglutinative LanguagesCode0
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research—0
Bringing Order to Neural Word Embeddings with Embeddings Augmented by Random Permutations (EARP)—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
Improved Dependency Parsing using Implicit Word Connections Learned from Unlabeled Data—0
Linking News Sentiment to Microblogs: A Distributional Semantics Approach to Enhance Microblog Sentiment Classification—0
Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings—0
Show:102550
← PrevPage 98 of 161Next →

No leaderboard results yet.