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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

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Showing 2451–2500 of 4002 papers

TitleStatusHype
Predicting News Headline Popularity with Syntactic and Semantic Knowledge Using Multi-Task Learning—0
The Lazy Encoder: A Fine-Grained Analysis of the Role of Morphology in Neural Machine Translation—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
Modeling Input Uncertainty in Neural Network Dependency ParsingCode0
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings—0
InferLite: Simple Universal Sentence Representations from Natural Language Inference Data—0
Quantifying Context Overlap for Training Word Embeddings—0
Unsupervised Bilingual Lexicon Induction via Latent Variable Models—0
A Framework for Understanding the Role of Morphology in Universal Dependency Parsing—0
Synthetic Data Made to Order: The Case of ParsingCode0
Syntax Encoding with Application in Authorship Attribution—0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Improved Dependency Parsing using Implicit Word Connections Learned from Unlabeled Data—0
Word Embeddings for Code-Mixed Language Processing—0
Learning Unsupervised Word Translations Without Adversaries—0
How to represent a word and predict it, too: Improving tied architectures for language modelling—0
Streaming word similarity mining on the cheap—0
Refining Pretrained Word Embeddings Using Layer-wise Relevance Propagation—0
A Neural Local Coherence Model for Text Quality Assessment—0
Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources—0
Part-of-Speech Tagging for Code-Switched, Transliterated Texts without Explicit Language Identification—0
Auto-Encoding Dictionary Definitions into Consistent Word EmbeddingsCode0
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images—0
Siamese Network-Based Supervised Topic Modeling—0
Genre Separation Network with Adversarial Training for Cross-genre Relation Extraction—0
Similarity-Based Reconstruction Loss for Meaning Representation—0
Parameter-free Sentence Embedding via Orthogonal BasisCode0
Semi-supervised Learning with Multi-Domain Sentiment Word Embeddings—0
Using Word Embeddings to Explore the Learned Representations of Convolutional Neural Networks—0
BLISS in Non-Isometric Embedding Spaces—0
Consistency and Variation in Kernel Neural Ranking Model—0
Predictive Embeddings for Hate Speech Detection on Twitter—0
Learning and Evaluating Sparse Interpretable Sentence Embeddings—0
Predicting the Argumenthood of English Prepositional Phrases—0
FRAGE: Frequency-Agnostic Word RepresentationCode0
Meta-Embedding as Auxiliary Task Regularization—0
Macquarie University at BioASQ 6b: Deep learning and deep reinforcement learning for query-based multi-document summarisation—0
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional NetworksCode0
Generalizing Word Embeddings using Bag of SubwordsCode0
Distilled Wasserstein Learning for Word Embedding and Topic Modeling—0
AWE: Asymmetric Word Embedding for Textual Entailment—0
Unsupervised Cross-lingual Transfer of Word Embedding SpacesCode0
xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense NetworksCode0
SHOMA at Parseme Shared Task on Automatic Identification of VMWEs: Neural Multiword Expression Tagging with High GeneralisationCode0
Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model—0
Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models—0
Learning Embeddings of Directed Networks with Text-Associated Nodes---with Applications in Software Package Dependency Networks—0
Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluationCode0
An Analysis of Hierarchical Text Classification Using Word Embeddings—0
Sentylic at IEST 2018: Gated Recurrent Neural Network and Capsule Network Based Approach for Implicit Emotion Detection—0
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