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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 2726–2750 of 4002 papers

TitleStatusHype
Where's the Learning in Representation Learning for Compositional Semantics and the Case of Thematic Fit—0
Which Evaluations Uncover Sense Representations that Actually Make Sense?—0
Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models—0
Whom to Learn From? Graph- vs. Text-based Word Embeddings—0
Why does PairDiff work? - A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
Why is unsupervised alignment of English embeddings from different algorithms so hard?—0
Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries—0
Why PairDiff works? -- A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations—0
“Wikily” Supervised Neural Translation Tailored to Cross-Lingual Tasks—0
Wild Devs' at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity—0
With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation—0
WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive Language Identification in Code-switched YouTube Comments—0
WMDO: Fluency-based Word Mover's Distance for Machine Translation Evaluation—0
WOLVESAAR at SemEval-2016 Task 1: Replicating the Success of Monolingual Word Alignment and Neural Embeddings for Semantic Textual Similarity—0
Word2net: Deep Representations of Language—0
Word2rate: training and evaluating multiple word embeddings as statistical transitions—0
Word2Sense: Sparse Interpretable Word Embeddings—0
Word-Alignment-Based Segment-Level Machine Translation Evaluation using Word Embeddings—0
Word and Document Embeddings based on Neural Network Approaches—0
Word and Phrase Features in Graph Convolutional Network for Automatic Question Classification—0
Word associations and the distance properties of context-aware word embeddings—0
Word-Context Character Embeddings for Chinese Word Segmentation—0
WordDecipher: Enhancing Digital Workspace Communication with Explainable AI for Non-native English Speakers—0
Word Definitions from Large Language Models—0
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