pietrolesci/anchoral-paper-artefacts
收藏Hugging Face2024-04-08 更新2024-06-11 收录
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资源简介：
---
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.
--- 许可证：Apache-2.0 ---
本数据集收录与发表于NAACL 2024会议的论文《AnchorAL：面向大规模不平衡数据集的计算高效主动学习》相关的科研工件。上述科研工件可通过[github.com/pietrolesci/anchoral](https://github.com/pietrolesci/anchoral)提供的代码复现。
`outputs/` 文件夹包含各独立实验生成的原始文件。`results/` 文件夹存储了用于完成论文中数据分析、表格与图表绘制的导出指标及配置文件。
提供机构：
pietrolesci
原始信息汇总
数据集概述
数据集来源
- 该数据集与论文"AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets"相关，该论文发表于NAACL 2024会议。
数据集内容
outputs/文件夹：包含各个实验创建的原始文件。results/文件夹：包含用于完成分析并创建论文中报告的表格和图表的导出指标和配置。
许可证
- 本数据集遵循Apache-2.0许可证。
