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Samuel Larson

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#machine learning Preprint Sep 2026

Constant-Memory Recall: Learned Associations in a Fixed Matrix State

Fixed-size recurrent memory limits storage growth during inference, but successful recall depends on the task and training. We study a small DeltaNet variant with fixed token-specific key biases, trained to remember 32 new key-value pairings per sequence. With 32 KiB of recurrent matrix state, it achieves 99.95% mean a...

Samuel Larson · 0 citations

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