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Paper Citation Record · LEDGER

PCGRL: Procedural Content Generation via Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.09212.

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

pith.paper-citation-record.v1
2001.09212 v3

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:54:26.238255Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 16712606-3b2d-4d55-8dbf-e5eafbb88f26 · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution PCGRL: Procedural Content Generation via Reinforcement Learning

Reference 175

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:12:31.667254Z

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=arxiv_source observed=2026-05-16T08:12:30.984870Z digest=sha256:55ab4b48801691d36bfaeb97e227b02fba7ee974f62548bc46378244e97c44d9

Observation 329b4f62-dff8-4188-9e28-5e031643e1f9 · inbound

Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs cites this paper.

Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs PCGRL: Procedural Content Generation via Reinforcement Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-04T23:54:26.238255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:54:26.238255Z digest=sha256:bdf8296fda51ee87792b865927c2874315b9567edc5e0e96d4d7c88559060d6c