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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 1351–1400 of 4002 papers

TitleStatusHype
Cross-lingual Embeddings Reveal Universal and Lineage-Specific Patterns in Grammatical Gender Assignment—0
Pre-tokenization of Multi-word Expressions in Cross-lingual Word Embeddings—0
When is a bishop not like a rook? When it's like a rabbi! Multi-prototype BERT embeddings for estimating semantic relationshipsCode0
Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing—0
Analysing Word Representation from the Input and Output Embeddings in Neural Network Language ModelsCode0
Going Beyond T-SNE: Exposing whatlies in Text Embeddings—0
Understanding the Source of Semantic Regularities in Word Embeddings—0
WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive Language Identification in Code-switched YouTube Comments—0
Combining BERT with Static Word Embeddings for Categorizing Social Media—0
Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training—0
One of these words is not like the other: a reproduction of outlier identification using non-contextual word representationsCode0
From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers—0
How does BERT capture semantics? A closer look at polysemous wordsCode0
ESTeR: Combining Word Co-occurrences and Word Associations for Unsupervised Emotion DetectionCode0
Alignment-free Cross-lingual Semantic Role Labeling—0
Revisiting Representation Degeneration Problem in Language Modeling—0
Neutralizing Gender Bias in Word Embeddings with Latent Disentanglement and Counterfactual Generation—0
Embedding Structured Dictionary Entries—0
ISWARA at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings—0
Rethinking Topic Modelling: From Document-Space to Term-Space—0
Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words—0
Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgroupingCode0
Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings—0
Diachronic Embeddings for People in the News—0
Vocabulary Adaptation for Domain Adaptation in Neural Machine TranslationCode0
Beyond Adjacency Pairs: Hierarchical Clustering of Long Sequences for Human-Machine Dialogues—0
Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n\^6) down to O(n\^3)—0
Robust Backed-off Estimation of Out-of-Vocabulary Embeddings—0
The Chilean Waiting List Corpus: a new resource for clinical Named Entity Recognition in Spanish—0
Evaluating Word Embeddings on Low-Resource Languages—0
Evaluating Word Embeddings for Language Acquisition—0
Methods for Numeracy-Preserving Word Embeddings—0
Evaluating Bias In Dutch Word EmbeddingsCode0
"Thy algorithm shalt not bear false witness": An Evaluation of Multiclass Debiasing Methods on Word EmbeddingsCode0
A Cross-lingual Natural Language Processing Framework for Infodemic Management—0
Differential Privacy and Natural Language Processing to Generate Contextually Similar Decoy Messages in Honey Encryption Scheme—0
A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models—0
Learning Contextual Tag Embeddings for Cross-Modal Alignment of Audio and TagsCode0
Discovering and Interpreting Biased Concepts in Online CommunitiesCode0
Robust and Consistent Estimation of Word Embedding for Bangla Language by fine-tuning Word2Vec Model—0
Autoencoding Improves Pre-trained Word Embeddings—0
Contextualized Word Embeddings Encode Aspects of Human-Like Word Sense Knowledge—0
Word Embeddings for Chemical Patent Natural Language Processing—0
Anchor-based Bilingual Word Embeddings for Low-Resource Languages—0
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method—0
Topic Modeling with Contextualized Word Representation Clusters—0
Generating Adequate Distractors for Multiple-Choice Questions—0
Comparative analysis of word embeddings in assessing semantic similarity of complex sentences—0
Learning Graph-Based Priors for Generalized Zero-Shot Learning—0
On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition—0
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