AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets

8 April 2024

Papers citing "AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets"

7 / 7 papers shown

Title
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits Adit Jain Soumyabrata Pal Sunav Choudhary Ramasuri Narayanam Vikram Krishnamurthy 13 0 0 26 Oct 2024
On the Limitations of Simulating Active Learning Katerina Margatina Nikolaos Aletras 16 11 0 21 May 2023
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection Suchin Gururangan Dallas Card Sarah K. Drier E. K. Gade Leroy Z. Wang Zeyu Wang Luke Zettlemoyer Noah A. Smith 157 72 0 25 Jan 2022
Influence-Balanced Loss for Imbalanced Visual Classification Seulki Park Jongin Lim Younghan Jeon J. Choi CVBM 76 129 0 06 Oct 2021
Deduplicating Training Data Makes Language Models Better Katherine Lee Daphne Ippolito A. Nystrom Chiyuan Zhang Douglas Eck Chris Callison-Burch Nicholas Carlini SyDa 234 447 0 14 Jul 2021
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 104 180 0 19 Oct 2020
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 148 25,150 0 09 Jun 2011