metadata
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.
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.