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Paper Citation Record · LEDGER

Neural Replicator Dynamics

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1906.00190.

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

pith.paper-citation-record.v1
1906.00190 v5

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:15:24.583427Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:41:19.366021Z

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 050ff8f9-149a-48ad-8934-534fd6143121 · inbound

OpenSpiel: A Framework for Reinforcement Learning in Games cites this paper.

OpenSpiel: A Framework for Reinforcement Learning in Games Neural Replicator Dynamics

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-14T11:15:24.583427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:15:24.583427Z digest=sha256:44e5a317759807def477a09d6722a67e8b88f2d5164bb71827e2829a7f398a22

Observation e8bd2e1e-9a1d-4d8e-bf3e-e7939a5ca7fe · inbound

When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient cites this paper.

When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient Neural Replicator Dynamics

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:41:19.370655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T16:24:43.688967Z digest=sha256:49a216ea0c2bd2089149c6894db01c545c3ea505d0e7aed8c184fd5b10be62a7