18 citations · 27 across the 14 of their papers we have counts for
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cs.LG2026
BioDCASE: Active Learning for Bioacoustics
Ben McEwen, Rupa Kurinchi-Vendhan, Shiqi Zhang +3
Ecological monitoring increasingly relies on machine learning models, whose performance depends on the quality and quantity of labelled data. However, obtaining these labels is cos…
cs.LG2026
BoSS: A Best-of-Strategies Selector as an Oracle for Deep Active Learning
Denis Huseljic, Paul Hahn, Marek Herde +2
Active learning (AL) aims to reduce annotation costs while maximizing model performance by iteratively selecting valuable instances. While foundation models have made it easier to…