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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
Obtaining Better Static Word Embeddings Using Contextual Embedding ModelsCode1
OFA: A Framework of Initializing Unseen Subword Embeddings for Efficient Large-scale Multilingual Continued PretrainingCode1
Open-CyKG: An Open Cyber Threat Intelligence Knowledge GraphCode1
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling TasksCode1
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence InferenceCode1
Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic FormulaeCode1
PolyLM: Learning about Polysemy through Language ModelingCode1
Pre-training and Diagnosing Knowledge Base Completion ModelsCode1
Can a Fruit Fly Learn Word Embeddings?Code1
Probabilistic FastText for Multi-Sense Word EmbeddingsCode1
Quantifying the redundancy between prosody and textCode1
Query2Prod2Vec Grounded Word Embeddings for eCommerceCode1
Recovering Private Text in Federated Learning of Language ModelsCode1
Refinement of Unsupervised Cross-Lingual Word EmbeddingsCode1
Conditional probing: measuring usable information beyond a baselineCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
ADEPT: A DEbiasing PrompT FrameworkCode1
Revisiting Simple Neural Probabilistic Language ModelsCode1
SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation PurposesCode1
Self-Supervised Euphemism Detection and Identification for Content ModerationCode1
Semi-constraint Optimal Transport for Entity Alignment with Dangling CasesCode1
SemRe-Rank: Improving Automatic Term Extraction By Incorporating Semantic Relatedness With Personalised PageRankCode1
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like BiasesCode1
Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from SpeechCode1
GeDi: Generative Discriminator Guided Sequence GenerationCode1
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