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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 2501–2550 of 4002 papers

TitleStatusHype
Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models—0
Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell—0
Segmentation-free Compositional n-gram EmbeddingCode0
Affordance Extraction and Inference based on Semantic Role Labeling—0
Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural TherapyCode0
NTUA-SLP at IEST 2018: Ensemble of Neural Transfer Methods for Implicit Emotion ClassificationCode0
Why is unsupervised alignment of English embeddings from different algorithms so hard?—0
Gromov-Wasserstein Alignment of Word Embedding Spaces—0
Beyond Weight Tying: Learning Joint Input-Output Embeddings for Neural Machine TranslationCode0
Skip-gram word embeddings in hyperbolic spaceCode0
Learning Gender-Neutral Word EmbeddingsCode0
Neural Cross-Lingual Named Entity Recognition with Minimal ResourcesCode0
A Quantum Many-body Wave Function Inspired Language Modeling ApproachCode0
WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations—0
Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models—0
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword RepresentationsCode0
An Investigation of the Interactions Between Pre-Trained Word Embeddings, Character Models and POS Tags in Dependency Parsing—0
Predefined Sparseness in Recurrent Sequence ModelsCode0
Generating Text through Adversarial Training using Skip-Thought VectorsCode0
Unsupervised Multilingual Word EmbeddingsCode0
Dissecting Contextual Word Embeddings: Architecture and Representation—0
Improving Cross-Lingual Word Embeddings by Meeting in the MiddleCode0
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric ApproachCode0
Churn Intent Detection in Multilingual Chatbot Conversations and Social MediaCode0
Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition—0
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs—0
Reducing Gender Bias in Abusive Language Detection—0
The Influence of Down-Sampling Strategies on SVD Word Embedding Stability—0
SeVeN: Augmenting Word Embeddings with Unsupervised Relation VectorsCode0
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach—0
Syntree2Vec - An algorithm to augment syntactic hierarchy into word embeddings—0
Embedding Grammars—0
Angular-Based Word Meta-Embedding Learning—0
Unsupervised Keyphrase Extraction from Scientific PublicationsCode0
Learning to Represent Bilingual DictionariesCode0
Building a Kannada POS Tagger Using Machine Learning and Neural Network ModelsCode0
Word-Level Loss Extensions for Neural Temporal Relation ClassificationCode0
Instantiation—0
Using Word Embeddings for Unsupervised Acronym Disambiguation—0
Model-Free Context-Aware Word Composition—0
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena—0
A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction—0
AnlamVer: Semantic Model Evaluation Dataset for Turkish - Word Similarity and RelatednessCode0
Learning to Generate Word Representations using Subword Information—0
Modeling with Recurrent Neural Networks for Open Vocabulary Slots—0
Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings—0
Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological TagsCode0
What's in Your Embedding, And How It Predicts Task Performance—0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activationsCode0
Towards a unified framework for bilingual terminology extraction of single-word and multi-word termsCode0
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