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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 1726–1750 of 4002 papers

TitleStatusHype
Word Embedding based New Corpus for Low-resourced Language: Sindhi—0
DeFINE: DEep Factorized INput Token Embeddings for Neural Sequence ModelingCode1
Taking a Stance on Fake News: Towards Automatic Disinformation Assessment via Deep Bidirectional Transformer Language Models for Stance Detection—0
Word-Class Embeddings for Multiclass Text ClassificationCode0
Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes—0
City2City: Translating Place Representations across Cities—0
Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction—0
A Causal Inference Method for Reducing Gender Bias in Word Embedding RelationsCode0
Towards robust word embeddings for noisy textsCode0
Causally Denoise Word Embeddings Using Half-Sibling RegressionCode0
Enhancing Out-Of-Domain Utterance Detection with Data Augmentation Based on Word Embeddings—0
Anaphora Resolution in Dialogue Systems for South Asian Languages—0
Multilingual Culture-Independent Word Analogy Datasets—0
Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context—0
Empirical Autopsy of Deep Video Captioning Frameworks—0
SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word EmbeddingsCode0
Improving Document Classification with Multi-Sense EmbeddingsCode1
Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models—0
Bootstrapping NLU Models with Multi-task Learning—0
What do you mean, BERT? Assessing BERT as a Distributional Semantics Model—0
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis—0
Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence—0
How to Evaluate Word Representations of Informal Domain?Code0
word2ket: Space-efficient Word Embeddings inspired by Quantum EntanglementCode0
Contextualized End-to-End Neural Entity Linking—0
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