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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

Showing 13511400 of 4002 papers

TitleStatusHype
Adjusting Word Embeddings with Semantic Intensity Orders0
A Comparative Study of Neural Network Models for Sentence Classification0
4chan & 8chan embeddings0
Disentangling Latent Emotions of Word Embeddings on Complex Emotional Narratives0
Examining Structure of Word Embeddings with PCA0
Convolutional Neural Network for Universal Sentence Embeddings0
Attending Sentences to detect Satirical Fake News0
Contrastive Word Embedding Learning for Neural Machine Translation0
ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks0
Analyzing Acoustic Word Embeddings from Pre-trained Self-supervised Speech Models0
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations0
A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation0
Continuous Word Embedding Fusion via Spectral Decomposition0
A Transparent Framework for Evaluating Unintended Demographic Bias in Word Embeddings0
A Distribution-based Model to Learn Bilingual Word Embeddings0
Context Vectors are Reflections of Word Vectors in Half the Dimensions0
A Topical Approach to Capturing Customer Insight In Social Media0
Analysis of Word Embeddings Using Fuzzy Clustering0
CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning0
Contextualizing Citations for Scientific Summarization using Word Embeddings and Domain Knowledge0
Atalaya at TASS 2019: Data Augmentation and Robust Embeddings for Sentiment Analysis0
Contextualized Word Embeddings Enhanced Event Temporal Relation Extraction for Story Understanding0
Contextualized Word Embeddings Encode Aspects of Human-Like Word Sense Knowledge0
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification0
Analysis of Word Embeddings and Sequence Features for Clinical Information Extraction0
A Deterministic Algorithm for Bridging Anaphora Resolution0
Contextualized Spoken Word Representations from Convolutional Autoencoders0
Contextualized moral inference0
Contextualized Embeddings for Enriching Linguistic Analyses on Politeness0
Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing0
A System for Multilingual Dependency Parsing based on Bidirectional LSTM Feature Representations0
Contextualized context2vec0
Contextualization and Generalization in Entity and Relation Extraction0
Analysis of Italian Word Embeddings0
Contextual Embeddings: When Are They Worth It?0
Contextual Document Embeddings0
Asymmetric Proxy Loss for Multi-View Acoustic Word Embeddings0
Contextual Aware Joint Probability Model Towards Question Answering System0
Contextual and Position-Aware Factorization Machines for Sentiment Classification0
A Syllable-based Technique for Word Embeddings of Korean Words0
Analysis of Inferences in Chinese for Opinion Mining0
Contextual and Non-Contextual Word Embeddings: an in-depth Linguistic Investigation0
Context Sensitive Neural Lemmatization with Lematus0
Context-Sensitive Malicious Spelling Error Correction0
A Survey on Word Meta-Embedding Learning0
Analysis of Gender Bias in Social Perception and Judgement Using Chinese Word Embeddings0
A Deep Representation Empowered Distant Supervision Paradigm for Clinical Information Extraction0
A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions0
ConTextING: Granting Document-Wise Contextual Embeddings to Graph Neural Networks for Inductive Text Classification0
Context-Dependent Sense Embedding0
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