Papers with active learning or

1 papers
Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models (2024.emnlp-main)

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Challenge: Existing methods to train models without labeled data are lacking in supervised tasks . a lack of labeles is the main obstacle to real-world applications .
Approach: They propose a semi-supervised approach that uses a model to obtain pseudo-labels for unlabeled data.
Outcome: The proposed method outperforms the reproduced methods on four text classification benchmarks.

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