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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 1551–1575 of 4002 papers

TitleStatusHype
Fast query-by-example speech search using separable model—0
Fast Query Expansion on an Accounting Corpus using Sub-Word Embeddings—0
FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering—0
FBK HLT-MT at SemEval-2016 Task 1: Cross-lingual Semantic Similarity Measurement Using Quality Estimation Features and Compositional Bilingual Word Embeddings—0
Combining Character and Word Embeddings for the Detection of Offensive Language in Arabic—0
Extremely Small BERT Models from Mixed-Vocabulary Training—0
Combining BERT with Static Word Embeddings for Categorizing Social Media—0
Feature Engineering vs BERT on Twitter Data—0
A Sequence Learning Method for Domain-Specific Entity Linking—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages—0
Fermi at SemEval-2017 Task 7: Detection and Interpretation of Homographic puns in English Language—0
Addressing Low-Resource Scenarios with Character-aware Embeddings—0
A Chinese Writing Correction System for Learning Chinese as a Foreign Language—0
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF—0
Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages—0
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains—0
Field Embedding: A Unified Grain-Based Framework for Word Representation—0
Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words—0
Figure Me Out: A Gold Standard Dataset for Metaphor Interpretation—0
Extremal GloVe: Theoretically Accurate Distributed Word Embedding by Tail Inference—0
Finding Individual Word Sense Changes and their Delay in Appearance—0
Finding People's Professions and Nationalities Using Distant Supervision - The FMI@SU "goosefoot" team at the WSDM Cup 2017 Triple Scoring Task—0
Fine-Grained Contextual Predictions for Hard Sentiment Words—0
Extrapolating Binder Style Word Embeddings to New Words—0
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