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Paper Citation Record · LEDGER

Can Large Language Models Help Developers with Robotic Finite State Machine Modification?

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.05625.

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

pith.paper-citation-record.v1
2412.05625 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 2026-08-06T17:17:29.687007Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T04:55:03.952180Z

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 e85afc62-f0d6-4dbb-9495-966914d220e0 · inbound

An Agentic Flow for Finite State Machine Extraction using Prompt Chaining cites this paper.

An Agentic Flow for Finite State Machine Extraction using Prompt Chaining Can Large Language Models Help Developers with Robotic Finite State Machine Modification?

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T17:17:29.687007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:17:29.687007Z digest=sha256:b7fd64b4c6cc01a3874be9701588b5b3492f1764e79fedb4b9c551447accd07f

Observation bcbdf553-11bf-4d23-a0fd-a3db9aa4f6c3 · inbound

BOOKMARKS: Efficient Active Storyline Memory for Role-playing cites this paper.

BOOKMARKS: Efficient Active Storyline Memory for Role-playing Can Large Language Models Help Developers with Robotic Finite State Machine Modification?

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-15T04:55:03.955650Z

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=2026-05-15T04:51:44.394368Z digest=sha256:808c12757bb8c44269812c47757cee32279c6f100abd8232048936b4c41640c0

Observation 42874eb6-adbe-47e9-87b3-1ccb70313977 · inbound

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning cites this paper.

A Generative Partially Specified Finite State Machine Approach to Complex Behaviour Planning Can Large Language Models Help Developers with Robotic Finite State Machine Modification?

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-01T22:39:17.160688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:39:17.160688Z digest=sha256:e699d4b5632b216f77377744471581e229aec2486e4ac819895f6c98972862d2