One external n-gram memory table, two exits for frozen LLMs: distribution fusion (quality) and speculative drafting (speed), with cheap alignment probes that predict when each pays.
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Updated
Oct 11, 2026 - Python
One external n-gram memory table, two exits for frozen LLMs: distribution fusion (quality) and speculative drafting (speed), with cheap alignment probes that predict when each pays.
Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models
TinyEngram — a 10-lab, test-driven course to implement DeepSeek Engram conditional memory from scratch: retrieval, gating, training, inference, and systems optimization.
Engram conditional-memory sparse LLM framework
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