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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
Derivational Morphological Relations in Word Embeddings—0
Czech Historical Named Entity Corpus v 1.0—0
DAG-based Long Short-Term Memory for Neural Word Segmentation—0
Biomedical Question Answering via Weighted Neural Network Passage Retrieval—0
Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings—0
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space—0
Data-Driven Mitigation of Adversarial Text Perturbation—0
Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing—0
Data Filtering using Cross-Lingual Word Embeddings—0
A Hierarchical Knowledge Representation for Expert Finding on Social Media—0
Data Sets: Word Embeddings Learned from Tweets and General Data—0
Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia—0
DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison—0
DCC-Uchile at SemEval-2020 Task 1: Temporal Referencing Word Embeddings—0
DCU: Using Distributional Semantics and Domain Adaptation for the Semantic Textual Similarity SemEval-2015 Task 2—0
An efficient domain-independent approach for supervised keyphrase extraction and ranking—0
Debiasing Embeddings for Reduced Gender Bias in Text Classification—0
Automatic Generation of Multiple-Choice Questions—0
Bio-inspired Structure Identification in Language Embeddings—0
Debiasing Pretrained Text Encoders by Paying Attention to Paying Attention—0
Automatic Labeling of Problem-Solving Dialogues for Computational Microgenetic Learning Analytics—0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
Automatic Learning of Modality Exclusivity Norms with Crosslingual Word Embeddings—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
A Note on Argumentative Topology: Circularity and Syllogisms as Unsolved Problems—0
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