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FAAST: Forward-Only Associative Learning via Closed-Form Fast Weights for Test-Time Supervised Adaptation

Hugging Face Daily Papers · 2026-05-08 Cached

FAAST proposes a forward-only method that compiles labeled examples into fast weights analytically, enabling efficient test-time supervised adaptation without backpropagation, achieving over 90% speedup and 95% memory savings while maintaining performance.

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