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Paper Citation Record · LEDGER

Reinforcement learning for graph theory, I. Reimplementation of Wagner's approach

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.18429.

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

pith.paper-citation-record.v1
2403.18429 v2

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:25:56.732575Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T13:22:55.190594Z

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 fc876007-75a3-4c84-8453-e823ebe38bb2 · inbound

Reinforcement learning for graph theory, Parallelizing Wagner's approach cites this paper.

Reinforcement learning for graph theory, Parallelizing Wagner's approach Reinforcement learning for graph theory, I. Reimplementation of Wagner's approach

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T12:25:56.732575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:25:56.732575Z digest=sha256:e519f25a740435abbd7553418dee7513b127bbe44e0664f2d5cb5f6a68b8ec58

Observation 08e8ed54-71cf-4e66-bb61-e4c5ed9bb4b0 · inbound

A Genetic Algorithm for Generating Extreme Examples in Arithmetic Dynamics cites this paper.

A Genetic Algorithm for Generating Extreme Examples in Arithmetic Dynamics Reinforcement learning for graph theory, I. Reimplementation of Wagner's approach

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:22:55.192998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T13:22:51.651262Z digest=sha256:59b56e4013b6905912be9319ceb0592e8b149a4fa0657c55cf0c504fd1f026bd