# When does Active Learning Work?

arXiv: https://arxiv.org/abs/1408.1319 · HTML: https://mlsanity.com/paper/1408.1319/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Aug 2014.

## Built on by (most cited first, 3 of 3)

- [ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data](https://mlsanity.com/paper/2406.17322/) (2024)
- [Active Learning Methods for Efficient Data Utilization and Model Performance Enhancement](https://mlsanity.com/paper/2504.16136/) (2025)
- [Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid](https://mlsanity.com/paper/2506.03817/) (2025)

## Abstract (arXiv)

Active Learning (AL) methods seek to improve classifier performance when labels are expensive or scarce. We consider two central questions: Where does AL work? How much does it help? To address these questions, a comprehensive experimental simulation study of Active Learning is presented. We consider a variety of tasks, classifiers and other AL factors, to present a broad exploration of AL performance in various settings. A precise way to quantify performance is needed in order to know when AL works. Thus we also present a detailed methodology for tackling the complexities of assessing AL performance in the context of this experimental study.