Papers with bootstrap training

2 papers
Prototype-Representations for Training Data Filtering in Weakly-Supervised Information Extraction (2022.emnlp-industry)

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Challenge: Weak supervision and data programming are powerful tools to support information extraction models.
Approach: They propose a prototype-based method to denoise weakly supervised training data . they use a model to model the correct contexts for a given target value .
Outcome: The proposed method achieves 9% accuracy gain in attribute value extraction in e-commerce websites.
Recurrent Neural Networks with Mixed Hierarchical Structures and EM Algorithm for Natural Language Processing (2022.lrec-1)

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Challenge: A variety of hierarchical RNN models have been proposed to incorporate hierarchically-based hierarchic information in modeling languages in the literature.
Approach: They propose a latent indicator layer approach to identify and learn hierarchical information and develop an EM algorithm to handle the latent indicators layer in training.
Outcome: The proposed approach outperforms other RNN-based models in document classification tasks.

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