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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 2576–2600 of 4002 papers

TitleStatusHype
Unsupervised Learning of Style-sensitive Word Vectors—0
Unsupervised Mitigating Gender Bias by Character Components: A Case Study of Chinese Word Embedding—0
Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings—0
Unsupervised Morphology Induction Using Word Embeddings—0
Unsupervised Most Frequent Sense Detection using Word Embeddings—0
Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge—0
Unsupervised Parallel Sentence Extraction from Comparable Corpora—0
Unsupervised POS Induction with Word Embeddings—0
Unsupervised Random Walk Sentence Embeddings: A Strong but Simple Baseline—0
Unsupervised Sentence Representations as Word Information Series: Revisiting TF--IDF—0
Unsupervised Summarization by Jointly Extracting Sentences and Keywords—0
Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddings—0
Unsupervised Word Mapping Using Structural Similarities in Monolingual Embeddings—0
Unsupervised word segmentation and lexicon discovery using acoustic word embeddings—0
Unsupervised Word Translation Pairing using Refinement based Point Set Registration—0
Unsupervised Word Translation with Adversarial Autoencoder—0
UNT Linguistics at SemEval-2020 Task 12: Linear SVC with Pre-trained Word Embeddings as Document Vectors and Targeted Linguistic Features—0
Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation—0
UPB at SemEval-2020 Task 9: Identifying Sentiment in Code-Mixed Social Media Texts using Transformers and Multi-Task Learning—0
UPB at SemEval-2021 Task 1: Combining Deep Learning and Hand-Crafted Features for Lexical Complexity Prediction—0
Upgrading the Newsroom: An Automated Image Selection System for News Articles—0
Uppsala University at SemEval-2022 Task 1: Can Foreign Entries Enhance an English Reverse Dictionary?—0
UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post's Nesting and Syntax Information for Rumor Stance Classification—0
Urban Dictionary Embeddings for Slang NLP Applications—0
USAAR at SemEval-2016 Task 13: Hyponym Endocentricity—0
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