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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 476–500 of 4002 papers

TitleStatusHype
Raccoons at SemEval-2022 Task 11: Leveraging Concatenated Word Embeddings for Named Entity Recognition—0
Subword-based Cross-lingual Transfer of Embeddings from Hindi to Marathi and Nepali—0
Cross-Language Transfer of High-Quality Annotations: Combining Neural Machine Translation with Cross-Linguistic Span Alignment to Apply NER to Clinical Texts in a Low-Resource LanguageCode0
Team Stanford ACMLab at SemEval 2022 Task 4: Textual Analysis of PCL Using Contextual Word Embeddings—0
An Empirical Study on the Fairness of Pre-trained Word Embeddings—0
Interpreting Emoji with Emoji—0
Leveraging Three Types of Embeddings from Masked Language Models in Idiom Token Classification—0
When Polysemy Matters: Modeling Semantic Categorization with Word Embeddings—0
How direct is the link between words and images?—0
Using BERT Embeddings to Model Word Importance in Conversational Transcripts for Deaf and Hard of Hearing Users—0
Language with Vision: a Study on Grounded Word and Sentence EmbeddingsCode0
niksss at HinglishEval: Language-agnostic BERT-based Contextual Embeddings with Catboost for Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish TextCode0
TransDrift: Modeling Word-Embedding Drift using Transformer—0
JU_NLP at HinglishEval: Quality Evaluation of the Low-Resource Code-Mixed Hinglish Text—0
Contextualization and Generalization in Entity and Relation Extraction—0
Zero-shot object goal visual navigationCode1
HICEM: A High-Coverage Emotion Model for Artificial Emotional Intelligence—0
Transition-based Abstract Meaning Representation Parsing with Contextual Embeddings—0
1Cademy at Semeval-2022 Task 1: Investigating the Effectiveness of Multilingual, Multitask, and Language-Agnostic Tricks for the Reverse Dictionary Task—0
Gender Bias in Word Embeddings: A Comprehensive Analysis of Frequency, Syntax, and Semantics—0
Comparing Performance of Different Linguistically-Backed Word Embeddings for Cyberbullying Detection—0
Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender SignalsCode0
Tracking Changes in ESG Representation: Initial Investigations in UK Annual Reports—0
Dialects Identification of Armenian Language—0
Use Case: Romanian Language Resources in the LOD Paradigm—0
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