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Advformer: A Neural Network Architecture for Correcting Korean Spacing Error Using Adversarial Perturbation

https://doi.org/10.2139/ssrn.4797899
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Application of a Hybrid Bi-LSTM-CRF Model to the Task of Russian Named Entity Recognition
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End-to-End Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-Level Vs. Character-Level
inferredcites →https://doi.org/10.1007/s10462-019-09784-7openalex-extracted
A survey of regularization strategies for deep models
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Character-level neural network for biomedical named entity recognition
inferredcites →https://doi.org/10.1109/iccv.2019.00381openalex-extracted
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
inferredcites →https://doi.org/10.1109/tip.2021.3089942openalex-extracted
Delving Deep Into Label Smoothing
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Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
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ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1162/tacl_a_00104openalex-extracted
Named Entity Recognition with Bidirectional LSTM-CNNs
inferredcites →https://doi.org/10.1186/1472-6947-15-s1-s9openalex-extracted
Developing a hybrid dictionary-based bio-entity recognition technique
inferredcites →https://doi.org/10.1609/aaai.v30i1.10202openalex-extracted
Shakeout: A New Regularized Deep Neural Network Training Scheme
inferredcites →https://doi.org/10.1609/aaai.v32i1.11768openalex-extracted
Orthogonal Weight Normalization: Solution to Optimization Over Multiple Dependent Stiefel Manifolds in Deep Neural Networks
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.552openalex-extracted
SimCSE: Simple Contrastive Learning of Sentence Embeddings
inferredcites →https://doi.org/10.18653/v1/2022.findings-emnlp.278openalex-extracted
An Error-Guided Correction Model for Chinese Spelling Error Correction
inferredcites →https://doi.org/10.18653/v1/d18-1477openalex-extracted
Simple Recurrent Units for Highly Parallelizable Recurrence
inferredcites →https://doi.org/10.18653/v1/n16-1030openalex-extracted
Neural Architectures for Named Entity Recognition
inferredcites →https://doi.org/10.18653/v1/p16-1101openalex-extracted
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
inferredcites →https://doi.org/10.3390/app13052849openalex-extracted
A Chinese Named Entity Recognition Method Based on ERNIE-BiLSTM-CRF for Food Safety Domain
inferredcites →https://doi.org/10.3390/math10091386openalex-extracted
Leveraging Part-of-Speech Tagging Features and a Novel Regularization Strategy for Chinese Medical Named Entity Recognition
inferredcites →https://doi.org/10.3390/s22176652openalex-extracted
HAT4RD: Hierarchical Adversarial Training for Rumor Detection in Social Media
inferredcites →https://doi.org/10.3929/ethz-b-000460345openalex-extracted
Adversarial Training for Free!
inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-extracted
AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-extracted
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.48550/arxiv.1207.0580openalex-extracted
Improving neural networks by preventing co-adaptation of feature detectors
inferredcites →https://doi.org/10.48550/arxiv.1406.1831openalex-extracted
Analyzing noise in autoencoders and deep networks
inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-extracted
Neural Machine Translation by Jointly Learning to Align and Translate
inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-extracted
Sequence to Sequence Learning with Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1412.6572openalex-extracted
Explaining and Harnessing Adversarial Examples
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1602.07868openalex-extracted
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1603.01354openalex-extracted
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
inferredcites →https://doi.org/10.48550/arxiv.1605.07725openalex-extracted
Adversarial Training Methods for Semi-Supervised Text Classification
inferredcites →https://doi.org/10.48550/arxiv.1606.00189openalex-extracted
Neural Network Translation Models for Grammatical Error Correction
inferredcites →https://doi.org/10.48550/arxiv.1608.03665openalex-extracted
Learning Structured Sparsity in Deep Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1608.06757openalex-extracted
Robust Named Entity Recognition in Idiosyncratic Domains
inferredcites →https://doi.org/10.48550/arxiv.1909.11764openalex-extracted
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
inferredcites →https://doi.org/10.48550/arxiv.2001.01900openalex-extracted
Regularization via Structural Label Smoothing
inferredcites →https://doi.org/10.48550/arxiv.2106.14448openalex-extracted
R-Drop: Regularized Dropout for Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2108.12805openalex-extracted
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.2110.00425openalex-extracted
HAT4RD: Hierarchical Adversarial Training for Rumor Detection on Social Media
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