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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 976–1000 of 4002 papers

TitleStatusHype
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words ExtractionCode0
Automatic Transformation of Clinical Narratives into Structured Format—0
Position Masking for Improved Layout-Aware Document Understanding—0
Siamese Networks for Inference in Malayalam Language Texts—0
The Impact of Word Embeddings on Neural Dependency Parsing—0
Multilingual Learning for Mild Cognitive Impairment Screening from a Clinical Speech Task—0
A Deep Learning System for Automatic Extraction of Typological Linguistic Information from Descriptive Grammars—0
Comparing Contextual and Static Word Embeddings with Small Data—0
Abstractive Document Summarization with Word Embedding Reconstruction—0
Bilingual Terminology Extraction Using Neural Word Embeddings on Comparable Corpora—0
Syntax-aware Transformers for Neural Machine Translation: The Case of Text to Sign Gloss TranslationCode0
Event Prominence Extraction Combining a Knowledge-Based Syntactic Parser and a BERT Classifier for Dutch—0
Word Discriminations for Vocabulary Inventory PredictionCode0
Effectiveness of Deep Networks in NLP using BiDAF as an example architecture—0
Sense representations for Portuguese: experiments with sense embeddings and deep neural language models—0
Opinions are Made to be Changed: Temporally Adaptive Stance ClassificationCode0
Sarcasm Detection in Twitter -- Performance Impact while using Data Augmentation: Word EmbeddingsCode0
Yseop at FinSim-3 Shared Task 2021: Specializing Financial Domain Learning with Phrase Representations—0
How Cute is Pikachu? Gathering and Ranking Pokémon Properties from Data with Pokémon Word Embeddings—0
FeelsGoodMan: Inferring Semantics of Twitch Neologisms—0
Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021): Workshop and Shared Task Report—0
Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political BiasesCode0
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound—0
Efficacy of BERT embeddings on predicting disaster from Twitter dataCode0
Deriving Disinformation Insights from Geolocalized Twitter CalloutsCode0
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