most citedALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP

1 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2024★ 1 cited

Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Tasks

Philipp Kohl, Yoka Krämer, Claudia Fohry +1

We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows: Ob…

cs.CL2023★ 1 cited

ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP

Philipp Kohl, Nils Freyer, Yoka Krämer +5

Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate t…