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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 2251–2300 of 4002 papers

TitleStatusHype
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue systemCode0
On Measuring Social Biases in Sentence EncodersCode0
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings—0
LINSPECTOR: Multilingual Probing Tasks for Word RepresentationsCode0
Learning Entity Representations for Few-Shot Reconstruction of Wikipedia Categories—0
Personalized Neural Embeddings for Collaborative Filtering with Text—0
ETNLP: a visual-aided systematic approach to select pre-trained embeddings for a downstream taskCode0
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove ThemCode0
Context-Aware Cross-Lingual MappingCode0
Creation and Evaluation of Datasets for Distributional Semantics Tasks in the Digital Humanities Domain—0
Improving Cross-Domain Chinese Word Segmentation with Word EmbeddingsCode0
Russian Language Datasets in the Digitial Humanities Domain and Their Evaluation with Word EmbeddingsCode0
Using Word Embeddings for Visual Data Exploration with Ontodia and Wikidata—0
Relation Extraction Datasets in the Digital Humanities Domain and their Evaluation with Word Embeddings—0
Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corporaCode0
Efficient Contextual Representation Learning Without Softmax Layer—0
A Framework for Decoding Event-Related Potentials from Text—0
Still a Pain in the Neck: Evaluating Text Representations on Lexical CompositionCode0
SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular DataCode0
Interpretable Structure-aware Document Encoders with Hierarchical Attention—0
Context Vectors are Reflections of Word Vectors in Half the Dimensions—0
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency ParsingCode0
Leveraging Deep Graph-Based Text Representation for Sentiment Polarity Applications—0
VCWE: Visual Character-Enhanced Word EmbeddingsCode0
Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level RepresentationCode0
Enhancing Clinical Concept Extraction with Contextual Embeddings—0
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space ModelCode0
Learned In Speech Recognition: Contextual Acoustic Word Embeddings—0
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media—0
Contextual Word Representations: A Contextual IntroductionCode1
Categorical Metadata Representation for Customized Text ClassificationCode0
Wasserstein Barycenter Model EnsemblingCode0
Word embeddings for idiolect identification—0
Humor in Word Embeddings: Cockamamie Gobbledegook for NincompoopsCode0
Multi-task Learning for Target-dependent Sentiment ClassificationCode0
Word Embeddings for Entity-annotated TextsCode0
A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases—0
Understanding Composition of Word Embeddings via Tensor DecompositionCode0
Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey—0
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some MisconceptionsCode0
A Simple Regularization-based Algorithm for Learning Cross-Domain Word Embeddings—0
Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements—0
No Training Required: Exploring Random Encoders for Sentence ClassificationCode0
Evaluating Word Embedding Models: Methods and Experimental Results—0
Analogies Explained: Towards Understanding Word Embeddings—0
Word Embeddings: A Survey—0
MORTY Embedding: Improved Embeddings without Supervision—0
Context-Sensitive Malicious Spelling Error Correction—0
Equalizing Gender Biases in Neural Machine Translation with Word Embeddings TechniquesCode0
Deconstructing Word Embeddings—0
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