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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 17761800 of 4002 papers

TitleStatusHype
A Distribution-based Model to Learn Bilingual Word Embeddings0
A Transparent Framework for Evaluating Unintended Demographic Bias in Word Embeddings0
Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings0
Identification of Indigenous Knowledge Concepts through Semantic Networks, Spelling Tools and Word Embeddings0
Identifying Aggression and Toxicity in Comments using Capsule Network0
Identifying and interpreting non-aligned human conceptual representations using language modeling0
Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings0
Identifying attack and support argumentative relations using deep learning0
Identifying Cognates in English-Dutch and French-Dutch by means of Orthographic Information and Cross-lingual Word Embeddings0
Identifying Reference Spans: Topic Modeling and Word Embeddings help IR0
Identity-sensitive Word Embedding through Heterogeneous Networks0
Igbo Diacritic Restoration using Embedding Models0
Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes0
Convolutional Neural Network for Universal Sentence Embeddings0
IITK at the FinSim Task: Hypernym Detection in Financial Domain via Context-Free and Contextualized Word Embeddings0
Des pseudo-sens pour am\'eliorer l'extraction de synonymes \`a partir de plongements lexicaux (Pseudo-senses for improving the extraction of synonyms from word embeddings)0
IITPB at SemEval-2017 Task 5: Sentiment Prediction in Financial Text0
Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search0
Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentation0
Image Captioning with Visual Object Representations Grounded in the Textual Modality0
Convolutional Neural Networks for Sentiment Analysis on Weibo Data: A Natural Language Processing Approach0
Impact of Gender Debiased Word Embeddings in Language Modeling0
Impart Contextualization to Static Word Embeddings through Semantic Relations0
Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization0
Designing a Russian Idiom-Annotated Corpus0
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