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---
license: apache-2.0
---

Artefacts related to the paper "AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets" published at the NAACL 2024 conference.
These artefacts can be reproduced using the code available at [github.com/pietrolesci/anchoral](https://github.com/pietrolesci/anchoral).

The `outputs/` folder includes the raw files created by the individual experiments.
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.