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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 2026–2050 of 4002 papers

TitleStatusHype
Disunited Nations? A Multiplex Network Approach to Detecting Preference Affinity Blocs using Texts and Votes—0
Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?—0
DLRG@DravidianLangTech-ACL2022: Abusive Comment Detection in Tamil using Multilingual Transformer Models—0
DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings—0
DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction—0
DNN-Based Semantic Model for Rescoring N-best Speech Recognition List—0
Document Embedding for Scientific Articles: Efficacy of Word Embeddings vs TFIDF—0
Document-Level Machine Translation with Word Vector Models—0
Document-Level Sentiment Analysis of Urdu Text Using Deep Learning Techniques—0
Do Deep Learning Models and News Headlines Outperform Conventional Prediction Techniques on Forex Data?—0
Does History Matter? Using Narrative Context to Predict the Trajectory of Sentence Sentiment—0
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations—0
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations—0
Do gender neutral affixes naturally reduce gender bias in static word embeddings?—0
Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words—0
Domain Adaptation for Named Entity Recognition in Online Media with Word Embeddings—0
Domain adaptation for part-of-speech tagging of noisy user-generated text—0
Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval—0
Comparative analysis of word embeddings in assessing semantic similarity of complex sentences—0
Do Not Harm Protected Groups in Debiasing Language Representation Models—0
Do not neglect related languages: The case of low-resource Occitan cross-lingual word embeddings—0
Don't Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Don’t Forget Cheap Training Signals Before Building Unsupervised Bilingual Word Embeddings—0
Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects—0
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