CARE-DPP combines class-balanced uncertainty, annealed embedding novelty, and DPP-based batch diversification for bioacoustic active learning, achieving 0.50 mean AULC versus 0.46 for CoreSet.
Removing it reduces mean AULC from 0.50 to 0.46, with particularly large losses on HSN and UHH (Table 3)
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Determinantal point process sampling for bioacoustic active learning
CARE-DPP combines class-balanced uncertainty, annealed embedding novelty, and DPP-based batch diversification for bioacoustic active learning, achieving 0.50 mean AULC versus 0.46 for CoreSet.