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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 201–225 of 4002 papers

TitleStatusHype
Expressivity-aware Music Performance Retrieval using Mid-level Perceptual Features and Emotion Word Embeddings—0
Contrastive Learning in Distilled ModelsCode0
Multilingual acoustic word embeddings for zero-resource languages—0
GWPT: A Green Word-Embedding-based POS Tagger—0
Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed EmbeddingsCode0
Machine Learning to Promote Translational Research: Predicting Patent and Clinical Trial Inclusion in Dementia Research—0
Estimating Text Similarity based on Semantic Concept Embeddings—0
MoSECroT: Model Stitching with Static Word Embeddings for Crosslingual Zero-shot Transfer—0
Building Vision-Language Models on Solid Foundations with Masked Distillation—0
An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks—0
Effect of dimensionality change on the bias of word embeddings—0
Zur Darstellung eines mehrstufigen Prototypbegriffs in der multilingualen automatischen Sprachgenerierung: vom Korpus über word embeddings bis hin zum automatischen Wörterbuch—0
Multi-level biomedical NER through multi-granularity embeddings and enhanced labeling—0
Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models—0
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations—0
Decoupled Textual Embeddings for Customized Image GenerationCode1
Disentangling continuous and discrete linguistic signals in transformer-based sentence embeddings—0
Def2Vec: Extensible Word Embeddings from Dictionary DefinitionsCode0
Well-calibrated Confidence Measures for Multi-label Text Classification with a Large Number of Labels—0
Natural Language Processing for Diagnosis and Risk Assessment of Cardiovascular Disease—0
Where exactly does contextualization in a PLM happen?—0
Constructing Vec-tionaries to Extract Message Features from Texts: A Case Study of Moral Appeals—0
Unsupervised Approach to Evaluate Sentence-Level Fluency: Do We Really Need Reference?Code0
Robust Concept Erasure via Kernelized Rate-Distortion MaximizationCode0
Quantifying the redundancy between prosody and textCode1
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