
Nested Learning: Unifying Architecture and Optimization for Continual AI
152
Unify architecture and optimization as nested, multi-timescale learners to curb forgetting and enable continual learning, validated by the Hope model’s strong results.

Unify architecture and optimization as nested, multi-timescale learners to curb forgetting and enable continual learning, validated by the Hope model’s strong results.

Use sparse memory layers and TF-IDF–guided slot updates to learn continually without forgetting.