Selective Backpropagation for Efficient Few-Shot Class-Incremental Learning
arXiv:2610.04003v1 Announce Type: new Abstract: Few-Shot Class-Incremental Learning (FSCIL) requires models to continuously learn new classes from limited samples while retaining prior knowledge, under strict constraints on compute and memory. Existing approaches lie along a difficult trade-off: si…
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- 2026-10-06 04:00 · arXiv cs.LG
Selective Backpropagation for Efficient Few-Shot Class-Incremental Learning