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Paper Citation Record · LEDGER

Large Language Models as Planning Domain Generators

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.06650.

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

pith.paper-citation-record.v1
2405.06650 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-10T11:50:21.908637Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T11:57:03.409743Z

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 cdd5b7da-7412-4104-97b8-c40d0cac9e64 · inbound

Specification-Driven Generation and Evaluation of Discrete-Event World Models via the DEVS Formalism cites this paper.

Specification-Driven Generation and Evaluation of Discrete-Event World Models via the DEVS Formalism Large Language Models as Planning Domain Generators

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-22T10:21:23.768994Z

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=2026-05-22T10:21:13.963271Z digest=sha256:9e41626e424d6aa153ef1a13959be40a90653f664aa11faa2be81b3bf152da13

Observation b14434dd-71e2-463d-b1ec-2fc35170dac8 · inbound

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing cites this paper.

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing Large Language Models as Planning Domain Generators

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-07-10T11:57:03.411169Z

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=2026-07-10T11:50:21.908637Z digest=sha256:fcf10f45eb3c6b9e220dd541c35f11f0fdfcb7fd67ca35251ec63dc438e094a6