Task vector arithmetic on near-orthogonal bioacoustic models allows composing multi-taxa classifiers without data sharing, with asymmetric accuracy gains for underrepresented taxa.
Catastrophic forgetting in connectionist net- works
2 Pith papers cite this work. Polarity classification is still indexing.
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Speech-based depression detection models primarily learn speaker identity rather than depression biomarkers, with performance dropping sharply on unseen speakers even under adversarial training.
citing papers explorer
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Ecologically-Constrained Task Arithmetic for Multi-Taxa Bioacoustic Classifiers Without Shared Data
Task vector arithmetic on near-orthogonal bioacoustic models allows composing multi-taxa classifiers without data sharing, with asymmetric accuracy gains for underrepresented taxa.
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Who is Speaking or Who is Depressed? A Controlled Study of Speaker Leakage in Speech-Based Depression Detection
Speech-based depression detection models primarily learn speaker identity rather than depression biomarkers, with performance dropping sharply on unseen speakers even under adversarial training.