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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 3651–3700 of 4002 papers

TitleStatusHype
Dirichlet-Smoothed Word Embeddings for Low-Resource Settings—0
Disambiguated skip-gram model—0
Discourse Relation Sense Classification Using Cross-argument Semantic Similarity Based on Word Embeddings—0
Discovering Bilingual Lexicons in Polyglot Word Embeddings—0
Discovering linguistic (ir)regularities in word embeddings through max-margin separating hyperplanes—0
Discovering Stylistic Variations in Distributional Vector Space Models via Lexical Paraphrases—0
Discretely Coding Semantic Rank Orders for Supervised Image Hashing—0
Discrete Wavelet Transform for Efficient Word Embeddings and Sentence Encoding—0
Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches—0
Discriminative Pre-training for Low Resource Title Compression in Conversational Grocery—0
Disentangling continuous and discrete linguistic signals in transformer-based sentence embeddings—0
Dissecting Contextual Word Embeddings: Architecture and Representation—0
Distance Metric Learning for Aspect Phrase Grouping—0
Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá—0
Improving Word Embedding Factorization for Compression Using Distilled Nonlinear Neural Decomposition—0
Distilled embedding: non-linear embedding factorization using knowledge distillation—0
Distilled Wasserstein Learning for Word Embedding and Topic Modeling—0
Distilling Word Embeddings: An Encoding Approach—0
Distinguishing Japanese Non-standard Usages from Standard Ones—0
Distributed Prediction of Relations for Entities: The Easy, The Difficult, and The Impossible—0
Distributed Representations for Unsupervised Semantic Role Labeling—0
Distributed Vector Representations for Unsupervised Automatic Short Answer Grading—0
Distributed Training of Embeddings using Graph Analytics—0
Distributional Analysis of Polysemous Function Words—0
Distributional Hypernym Generation by Jointly Learning Clusters and Projections—0
Distributional Lesk: Effective Knowledge-Based Word Sense Disambiguation—0
Distributional regularities of verbs and verbal adjectives: Treebank evidence and broader implications—0
Distributional Representations of Words for Short Text Classification—0
Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach—0
Distributional Semantics for Neo-Latin—0
Distribution is not enough: going Firther—0
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
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