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license: apache-2.0 |
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Artefacts related to the paper "AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets" published at the NAACL 2024 conference. |
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These artefacts can be reproduced using the code available at [github.com/pietrolesci/anchoral](https://github.com/pietrolesci/anchoral). |
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The `outputs/` folder includes the raw files created by the individual experiments. |
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The `results/` folder contains the exported metrics and configurations that are used to complete the analysis and create the tables and plots reported in the paper. |
