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Paper Citation Record · LEDGER

Recurrent Neural Networks in the Eye of Differential Equations

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.12933.

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

pith.paper-citation-record.v1
1904.12933 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:42:29.860703Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T11:42:30.047462Z

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 30177bfa-91c4-4945-b659-b14d8bc972a5 · inbound

RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? cites this paper.

RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? Recurrent Neural Networks in the Eye of Differential Equations

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:42:30.053130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T11:42:29.860703Z digest=sha256:04351a85c20f218508cf2c78e02166db1378b11ad4d99a4c6e47f4ee2ab0482a

Observation 4f8e7e8c-36de-4dcd-a3c6-5afd6d1020f6 · inbound

Universal Approximation Theorems for Dynamical Systems with Infinite-Time Horizon Guarantees cites this paper.

Universal Approximation Theorems for Dynamical Systems with Infinite-Time Horizon Guarantees Recurrent Neural Networks in the Eye of Differential Equations

Reference 126

Resolution
unresolved
no resolver link, observed 2026-08-03T03:21:49.695246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:21:49.695246Z digest=sha256:56f6db3df80d3a9c656d7583d02bd8d38e46d40eb4007f7d3d73fb626ffd969c