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Paper Citation Record · LEDGER

A recurrent neural network without chaos

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1612.06212.

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

pith.paper-citation-record.v1
1612.06212 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:08.208585Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:51:45.024848Z

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 fba2e746-70a6-4557-81fb-d34e43992eee · inbound

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum cites this paper.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum A recurrent neural network without chaos

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T05:27:08.208585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:27:08.208585Z digest=sha256:1cb7222f0ae4a1271b88fd403a4d50c90cd282780533d6d42f5150d6ced2a2bc

Observation 60cc5dd8-d8fa-4a62-85cb-2a9832f545f0 · inbound

Algorithm Development in Neural Networks: Insights from the Streaming Parity Task cites this paper.

Algorithm Development in Neural Networks: Insights from the Streaming Parity Task A recurrent neural network without chaos

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:51:45.028992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:51:44.731232Z digest=sha256:bc0bf7452535258bf3b0cdc1f21a0f87008b1250b87d47b2225d1e47ca4fcadf

Observation 190f1e9e-c994-4fdb-8a01-295af1930f71 · inbound

Chaos-Free Networks are Stable Recurrent Neural Networks cites this paper.

Chaos-Free Networks are Stable Recurrent Neural Networks A recurrent neural network without chaos

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-14T21:32:19.367153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T21:32:19.367153Z digest=sha256:3027be1bd32e43eecce299570bb9069e714e759e2f97b0b353fe2f7b1846a7e0