Paper Citation Record · LEDGER

Mimetic Initialization Helps State Space Models Learn to Recall

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.11135.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2410.11135 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:10:15.924424Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-21T05:33:58.924574Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4cd7186e-8082-4322-a602-6b3ba074244d · inbound

An Uncertainty Principle for Linear Recurrent Neural Networks cites this paper.

An Uncertainty Principle for Linear Recurrent Neural Networks Mimetic Initialization Helps State Space Models Learn to Recall

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T22:10:15.924424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc63eed7-6988-4153-b294-136e72acccc7 · inbound

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers cites this paper.

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers Mimetic Initialization Helps State Space Models Learn to Recall

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T15:22:53.929903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8352b836-1a73-4105-a452-b2c059d7a6ec · inbound

Towards Understanding Self-Pretraining for Sequence Classification cites this paper.

Towards Understanding Self-Pretraining for Sequence Classification Mimetic Initialization Helps State Space Models Learn to Recall

Reference 121

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.925920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e1f6603d-1c03-4ca6-9b0d-f140ffaabc44 · inbound

SHiPPO: Recurrent Memory with Transported Polynomial Projections cites this paper.

SHiPPO: Recurrent Memory with Transported Polynomial Projections Mimetic Initialization Helps State Space Models Learn to Recall

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-12T05:11:52.395478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.