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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 2626–2650 of 4002 papers

TitleStatusHype
Improving Optimization in Models With Continuous Symmetry Breaking—0
Unsupervised Random Walk Sentence Embeddings: A Strong but Simple Baseline—0
Attention-based Semantic Priming for Slot-filling—0
Improving Neural Network Performance by Injecting Background Knowledge: Detecting Code-switching and Borrowing in Algerian texts—0
Neural Sparse Topical Coding—0
WordNet EmbeddingsCode0
A Hybrid Learning Scheme for Chinese Word Embedding—0
Word Embeddings-Based Uncertainty Detection in Financial Disclosures—0
Orthographic Features for Bilingual Lexicon Induction—0
Code-Switched Named Entity Recognition with Embedding Attention—0
Towards Understanding the Geometry of Knowledge Graph EmbeddingsCode0
A Deep Relevance Model for Zero-Shot Document FilteringCode0
Unsupervised Learning of Distributional Relation Vectors—0
A Multi-task Approach to Learning Multilingual Representations—0
Comparison of Representations of Named Entities for Document Classification—0
Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search—0
Loss Decomposition for Fast Learning in Large Output Spaces—0
Joint learning of frequency and word embeddings for multilingual readability assessment—0
Addressing Noise in Multidialectal Word Embeddings—0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages—0
Compositional Morpheme Embeddings with Affixes as Functions and Stems as Arguments—0
Searching for the X-Factor: Exploring Corpus Subjectivity for Word Embeddings—0
EmotionX-Area66: Predicting Emotions in Dialogues using Hierarchical Attention Network with Sequence Labeling—0
Connecting Supervised and Unsupervised Sentence Embeddings—0
Natural Language Inference with Definition Embedding Considering Context On the Fly—0
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