5 citations · 7 across the 10 of their papers we have counts for
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cs.CL2023
FreeAL: Towards Human-Free Active Learning in the Era of Large Language Models
Ruixuan Xiao, Yiwen Dong, Junbo Zhao +4
Collecting high-quality labeled data for model training is notoriously time-consuming and labor-intensive for various NLP tasks. While copious solutions, such as active learning fo…
cs.HC2023
Towards Long-term Annotators: A Supervised Label Aggregation Baseline
Haoyu Liu, Fei Wang, Minmin Lin +6
Relying on crowdsourced workers, data crowdsourcing platforms are able to efficiently provide vast amounts of labeled data. Due to the variability in the annotation quality of crow…
cs.LG2023★ 5 cited
InstanT: Semi-supervised Learning with Instance-dependent Thresholds
Muyang Li, Runze Wu, Haoyu Liu +4
Semi-supervised learning (SSL) has been a fundamental challenge in machine learning for decades. The primary family of SSL algorithms, known as pseudo-labeling, involves assigning…