A geometric-mean loss over softmax attention weights improves few-shot classification accuracy over arithmetic-mean losses.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Geometric Mean Improves Loss For Few-Shot Learning
A geometric-mean loss over softmax attention weights improves few-shot classification accuracy over arithmetic-mean losses.