Paper Citation Record · LEDGER

Simplifying and Understanding State Space Models with Diagonal Linear RNNs

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2212.00768.

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

pith.paper-citation-record.v1
2212.00768 v3

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 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:50:28.623895Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:33:58.926010Z

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 b2cc0ee2-3f25-4cf5-a715-9b04abd3b388 · inbound

Mamba: Linear-Time Sequence Modeling with Selective State Spaces cites this paper.

Mamba: Linear-Time Sequence Modeling with Selective State Spaces Simplifying and Understanding State Space Models with Diagonal Linear RNNs

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:53:06.632619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 22e3801c-b225-49bc-8bc2-f8d06774a95d · inbound

Adjoint sharding for very long context training of state space models cites this paper.

Adjoint sharding for very long context training of state space models Simplifying and Understanding State Space Models with Diagonal Linear RNNs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T22:50:28.623895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a0f0b83-566a-40fd-ac4d-435367b0ec70 · inbound

On the Expressivity of Selective State-Space Layers: A Multivariate Polynomial Approach cites this paper.

On the Expressivity of Selective State-Space Layers: A Multivariate Polynomial Approach Simplifying and Understanding State Space Models with Diagonal Linear RNNs

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T13:05:31.618527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f43994b-3bd0-463d-8421-e93db1e07789 · inbound

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

Towards Understanding Self-Pretraining for Sequence Classification Simplifying and Understanding State Space Models with Diagonal Linear RNNs

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.927639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.