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Meta-Learning for Real-World Class Incremental Learning: A Transformer-Based Approach

2024-02-28

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<title>Abstract</title> <p>Modern Natural Language Processing (NLP) state-of-the-art (SoTA) Deep Learning (DL) models have hundreds of millions of parameters, making them extremely complex. Large datasets are required for training these models, and while pretraining has reduced this requirement, human-labelled datasets are still necessary for fine-tuning. Few-Shot Learning (FSL) techniques, such as meta-learning,...

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Literature Corpus work: 6ed6e2ed-7f12-57ac-8075-a86924b977a7
DOI: 10.21203/rs.3.rs-3914152/v1

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