InternalsAcademic foundations

Academic foundations

We’ve tried to be honest about where ideas come from. If a feature has a paper, it’s listed here.

PaperConcept adoptedWhere in the code
TMEM (arXiv:2606.04536)Parametric memory via fast weight updatesrecall/trust-decay.ts
MemQ (arXiv:2605.08374)TD(λ) eligibility traces on provenance DAGgovernance/td-lambda
RecMem (arXiv:2605.16045)Recurrence-gated LLM invocationrecall/rerank.ts gating
HyperMem (arXiv:2604.08256)Hypergraph memory with n-ary hyperedgeshyperedge
DELTAMEM (arXiv:2606.03083)Residual trees for episodic delta-encodingepisode delta-encoding
UCE (arXiv:2606.02304)Typed evolvable knowledge units + schedulerthe 10 typed primitives
Useful Memories Become Faulty (arXiv:2605.12978)Consolidation trap → raw episodes as evidenceconsolidation/cluster.ts gate
CALMem (arXiv:2605.20724)Token-budget-adaptive injection depthrecall/render.ts
Experience Compression (arXiv:2604.15877)Cross-level adaptive compressionsummarisation
ACT-R (Anderson, 2004)Activation-based memory retrievalrecall/search.ts strength
Hebb (1949)Co-activation strengtheningmnemo_relation co-recall
STDP (Bi & Poo, 1998)Spike-timing dependent plasticityrelation directionality

Why this matters

Most “memory for agents” startups ship vibes. We ship citations and the tests to back them up. If a paper turns out to be wrong, we revisit the feature — but we don’t add features that lack a defensible source.

Adding new ones

PRs that introduce cognitive features must include:

  1. A citation to the paper or production system they derive from.
  2. An integration test that exercises the claimed behaviour.
  3. A benchmark line that shows the claimed savings.

The bar is high on purpose — the cognitive surface is where memory systems silently rot if you’re not careful.