pietrolesci/anchoral-paper-artefacts
Artefacts related to the paper AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets (Lesci and Vlachos, 2024) 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… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/anchoral-paper-artefacts.
Artefacts related to the paper AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets (Lesci and Vlachos, 2024) 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.