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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 2551–2600 of 4002 papers

TitleStatusHype
UniPi: Recognition of Mentions of Disorders in Clinical Text—0
UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification—0
Universal Joint Morph-Syntactic Processing: The Open University of Israel's Submission to The CoNLL 2017 Shared Task—0
Unsupervised Abbreviation Disambiguation Contextual disambiguation using word embeddings—0
Unsupervised Alignment of Distributional Word Embeddings—0
Unsupervised Bilingual Lexicon Induction via Latent Variable Models—0
Unsupervised Compositional Translation of Multiword Expressions—0
Unsupervised Construction of Knowledge Graphs From Text and Code—0
Unsupervised Cross-Lingual Part-of-Speech Tagging for Truly Low-Resource Scenarios—0
Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models—0
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces—0
Unsupervised Deep Cross-modality Spectral Hashing—0
Unsupervised detection of diachronic word sense evolution—0
Unsupervised Does Not Mean Uninterpretable: The Case for Word Sense Induction and Disambiguation—0
Unsupervised Domain Adaptation with Contrastive Learning for Cross-domain Chinese NER—0
Unsupervised domain-agnostic identification of product names in social media posts—0
Unsupervised Geometric and Topological Approaches for Cross-Lingual Sentence Representation and Comparison—0
Unsupervised Hyper-alignment for Multilingual Word Embeddings—0
Unsupervised Hyperalignment for Multilingual Word Embeddings—0
Unsupervised Induction of Compositional Types for English Adjective-Noun Pairs—0
Unsupervised Induction of Linguistic Categories with Records of Reading, Speaking, and Writing—0
Unsupervised Inference of Object Affordance from Text Corpora—0
Unsupervised Joint Training of Bilingual Word Embeddings—0
Unsupervised Learning of Distributional Relation Vectors—0
Unsupervised Learning of Entailment-Vector Word Embeddings—0
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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