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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 2901–2950 of 4002 papers

TitleStatusHype
Learning Covariate-Specific Embeddings with Tensor Decompositions—0
One-shot and few-shot learning of word embeddings—0
On the Use of Word Embeddings Alone to Represent Natural Language Sequences—0
Lifelong Word Embedding via Meta-Learning—0
Word2net: Deep Representations of Language—0
A Simple Fully Connected Network for Composing Word Embeddings from Characters—0
Comparison of Paragram and GloVe Results for Similarity Benchmarks—0
Unsupervised Learning of Entailment-Vector Word Embeddings—0
Initial Experiments in Data-Driven Morphological Analysis for Finnish—0
Sound Analogies with Phoneme Embeddings—0
Learning Representations Specialized in Spatial Knowledge: Leveraging Language and VisionCode0
Bootstrap Domain-Specific Sentiment Classifiers from Unlabeled Corpora—0
Evaluating the Stability of Embedding-based Word Similarities—0
Beyond Word Embeddings: Learning Entity and Concept Representations from Large Scale Knowledge Bases—0
Detecting Cross-Lingual Plagiarism Using Simulated Word Embeddings—0
Corpus specificity in LSA and Word2vec: the role of out-of-domain documents—0
Generative Adversarial Nets for Multiple Text CorporaCode0
Finding People's Professions and Nationalities Using Distant Supervision - The FMI@SU "goosefoot" team at the WSDM Cup 2017 Triple Scoring Task—0
Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study—0
Unsupervised Word Mapping Using Structural Similarities in Monolingual Embeddings—0
Beyond Word2Vec: Embedding Words and Phrases in Same Vector SpaceCode0
Conditional Generative Adversarial Networks for Emoji Synthesis with Word Embedding Manipulation—0
Social Emotion Mining Techniques for Facebook Posts Reaction PredictionCode0
Recognizing Plans by Learning Embeddings from Observed Action Distributions—0
AWE-CM Vectors: Augmenting Word Embeddings with a Clinical MetathesaurusCode0
Monolingual Embeddings for Low Resourced Neural Machine TranslationCode0
Leveraging Linguistic Resources for Improving Neural Text Classification—0
Context Selection for Embedding ModelsCode0
SentiNLP at IJCNLP-2017 Task 4: Customer Feedback Analysis Using a Bi-LSTM-CNN Model—0
YNU-HPCC at IJCNLP-2017 Task 5: Multi-choice Question Answering in Exams Using an Attention-based LSTM Model—0
LDCCNLP at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases Using Machine Learning—0
All-In-1 at IJCNLP-2017 Task 4: Short Text Classification with One Model for All Languages—0
MainiwayAI at IJCNLP-2017 Task 2: Ensembles of Deep Architectures for Valence-Arousal Prediction—0
Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification—0
The Sentimental Value of Chinese Sub-Character Components—0
Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity—0
An Exploration of Word Embedding Initialization in Deep-Learning Tasks—0
SPINE: SParse Interpretable Neural EmbeddingsCode0
Improving the Accuracy of Pre-trained Word Embeddings for Sentiment AnalysisCode0
Word Embeddings Quantify 100 Years of Gender and Ethnic StereotypesCode0
Intelligent Word Embeddings of Free-Text Radiology ReportsCode0
Acquiring Common Sense Spatial Knowledge through Implicit Spatial TemplatesCode0
Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings—0
An Unsupervised Approach for Mapping between Vector Spaces—0
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings—0
Convolutional Neural Network with Word Embeddings for Chinese Word SegmentationCode0
Bayesian Paragraph Vectors—0
Breaking the Softmax Bottleneck: A High-Rank RNN Language ModelCode0
Learning Multi-Modal Word Representation Grounded in Visual Context—0
The Lifted Matrix-Space Model for Semantic CompositionCode0
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