Methods › Natural Language Processing › Text Classification Models › ALDEN
ALDEN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
ALDEN, or Active Learning with DivErse iNterpretations, is an active learning approach for text classification. With local interpretations in DNNs, ALDEN identifies linearly separable regions of samples. Then, it selects samples according to their diversity of local interpretations and queries their labels.
Specifically, we first calculate the local interpretations in DNN for each sample as the gradient backpropagated from the final predictions to the input features. Then, we use the most diverse interpretation of words in a sample to measure its diverseness. Accordingly, we select unlabeled samples with the maximally diverse interpretations for labeling and retrain the model with these labeled samples.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Deep Active Learning for Text Classification with Diverse Interpretations 15 Aug 2021 · 0 repositories · arXiv:2108.10687
Tasks archive 2025-07-28
7 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Active Learning | 1 |
| Classification | 1 |
| Diversity | 1 |
| Informativeness | 1 |
| Sentence | 1 |
| Text Classification | 1 |
| text-classification | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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