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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

Showing 326350 of 4002 papers

TitleStatusHype
New Product Development (NPD) through Social Media-based Analysis by Comparing Word2Vec and BERT Word Embeddings0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition0
SimpLex: a lexical text simplification architectureCode0
Towards preserving word order importance through Forced InvalidationCode0
Investigating Graph Structure Information for Entity Alignment with Dangling Cases0
On Evaluation of Bangla Word Analogies0
Deep Learning for Opinion Mining and Topic Classification of Course Reviews0
Affect as a proxy for literary mood0
PWESuite: Phonetic Word Embeddings and Tasks They FacilitateCode1
Learning to Name Classes for Vision and Language Models0
A Survey on Contextualised Semantic Shift DetectionCode0
Automatic Generation of Multiple-Choice Questions0
CTRAN: CNN-Transformer-based Network for Natural Language UnderstandingCode1
Addressing Biases in the Texts using an End-to-End Pipeline Approach0
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein ProblemCode0
Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings0
LANDMARK: Language-guided Representation Enhancement Framework for Scene Graph GenerationCode1
Changes in Commuter Behavior from COVID-19 Lockdowns in the Atlanta Metropolitan Area0
Deep learning model for Mongolian Citizens Feedback Analysis using Word Vector Embeddings0
SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation PurposesCode1
RETVec: Resilient and Efficient Text VectorizerCode2
Exploring Category Structure with Contextual Language Models and Lexical Semantic Networks0
Evaluation of Word Embeddings for the Social Sciences0
Dialectograms: Machine Learning Differences between Discursive Communities0
Zero-Shot Learning for Requirements Classification: An Exploratory StudyCode0
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