Catalog Systems Recent method papers — theorized, no distinct product Memformer

Memformer

External key-value stores with similarity-based cache management; trained with Memory Replay Backpropagation.

Research code · Verified 2026-10-28 · fresh as of 2026-10-28 · 27 cited facts, 0 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Type
External KV + Memory Replay Backprop repo fix
Tier
T3
Section
Recent method papers — theorized, no distinct product
Created
2022-12 paper fix
Latest release
no-release no-release paper fix
License
MIT repo fix
GitHub
9★ Python repo fix
Pricing
not applicable — research paper fix
Funding
not applicable — not commercial fix
Freshness
2026-10-28 fix
Layer
agent-infra repo fix
Licensing
open-source repo fix

Memory taxonomy

storage
kv-cache
retrieval
attention
persistence
session
update
consolidation
unit
kv-token
governance
opaque
conflict
n/a

When to use

Optimised for: not applicable - research paper

Anti-fit: not applicable - research paper

Pros & cons

Pros

External KV stores with similarity-based cache management, trained with Memory Replay Backprop.

Cons

2020 paper — superseded in production by retrieval-augmented approaches.

Claims & capabilities

External dynamic memory transformer for sequence modeling; memory replay back-propagation (MRBP) for long-range BPTT. Headline: 8.1x less memory and 3.2x faster inference vs. standard Transformers with comparable performance; baseline: standard Transformers; primary dataset: not specified in abstract (long-sequence language modeling).

Technical surface

API surface
not applicable — research paper
Backend storage
not applicable — research paper
Deployment
not applicable — research paper
Embedding model
not applicable — research paper
Multi-tenancy
not applicable — research paper
MCP
not applicable — research paper, no deployed product
A2A
not applicable — research paper, no deployed product
OpenTelemetry
not applicable — research paper, no deployed product

Similar systems

Other recent method papers — theorized, no distinct product in the catalog, ranked by inbound references.

  • Compressive Transformer T3

    Maintains recent states in full resolution while compressing older memories with learned compression functions. DeepMind.

  • MemGPT v2 / agent-tools T3

    Already in catalog as the foundational MemGPT paper. Note: Letta is the productionised successor (cross-listed).

  • Transformer-XL T3

    Extends context through segment-level recurrence + caching of hidden states from prior segments. Foundational long-context architecture.

  • Generative Agents T3

    Park et al. — landmark agent-simulation paper. Reflection + memory stream + retrieval enable believable agent behavior.

  • MemoryBank T3

    Enhances LLMs with long-term memory. Early influential paper.

  • Reflexion T3

    Language agents with verbal reinforcement learning.

Sources (26 cited facts, 0 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-22
    • Lifecycle first recorded as “research-complete”
    #195

Related systems

References (1)

Referenced by (2)