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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 726–750 of 4002 papers

TitleStatusHype
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 EmbeddingsCode0
Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist NewspapersCode0
How Gender and Skin Tone Modifiers Affect Emoji Semantics in TwitterCode0
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical DataCode0
How to Evaluate Word Representations of Informal Domain?Code0
Deep Unordered Composition Rivals Syntactic Methods for Text ClassificationCode0
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsCode0
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword RepresentationsCode0
CLIP-Decoder : ZeroShot Multilabel Classification using Multimodal CLIP Aligned RepresentationCode0
Definition Frames: Using Definitions for Hybrid Concept RepresentationsCode0
Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention SelectionCode0
Argument from Old Man's View: Assessing Social Bias in ArgumentationCode0
Identification of Adjective-Noun Neologisms using Pretrained Language ModelsCode0
Interpretable Segmentation of Medical Free-Text Records Based on Word EmbeddingsCode0
Imparting Interpretability to Word Embeddings while Preserving Semantic StructureCode0
Dict2vec : Learning Word Embeddings using Lexical DictionariesCode0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data SetCode0
A Robust Bias Mitigation Procedure Based on the Stereotype Content ModelCode0
A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding SpacesCode0
CMCE at SemEval-2020 Task 1: Clustering on Manifolds of Contextualized Embeddings to Detect Historical Meaning ShiftsCode0
A Robust Hybrid Approach for Textual Document ClassificationCode0
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word VectorsCode0
End-to-end Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-level vs. Character-levelCode0
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as WellCode0
Deep Learning for Hate Speech Detection in TweetsCode0
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