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Paper Citation Record · LEDGER

Integrating LLMs for Explainable Fault Diagnosis in Complex Systems

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.06695.

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

pith.paper-citation-record.v1
2402.06695 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:34:18.734721Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:07:17.582394Z

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 b545fd90-71cd-45a3-bab6-cd1682f52f23 · inbound

Complex System Diagnostics Using a Knowledge Graph-Informed and Large Language Model-Enhanced Framework cites this paper.

Complex System Diagnostics Using a Knowledge Graph-Informed and Large Language Model-Enhanced Framework Integrating LLMs for Explainable Fault Diagnosis in Complex Systems

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:34:18.734721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:34:18.734721Z digest=sha256:28208b53f7db1d7001787ffcbca787812f253313ea02b673200b537d4501d820

Observation 8d6dbdf2-de13-4547-bc38-156049d32bdc · inbound

CAMB: A comprehensive industrial LLM benchmark on civil aviation maintenance cites this paper.

CAMB: A comprehensive industrial LLM benchmark on civil aviation maintenance Integrating LLMs for Explainable Fault Diagnosis in Complex Systems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T15:09:07.639590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:09:07.639590Z digest=sha256:d45e7a2fc1a5c517ea02a3d84bf087a20a5983a48d7850ad49e66f6d7b57f660

Observation e7fd83b3-6cb2-4607-a994-8682698d0373 · inbound

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control cites this paper.

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control Integrating LLMs for Explainable Fault Diagnosis in Complex Systems

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-05-21T17:00:24.049586Z

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=pdf_text observed=2026-05-21T16:57:19.490074Z digest=sha256:eac833eace89bad91eb82b05589b87a64eee0e885a3216203274a6d71db65317

Observation 15407a02-6e8e-46a7-bcd1-5febca511f77 · inbound

Overcoming the Regulatory Bottleneck via Agent-to-Agent Protocols: A Nuclear Case Study cites this paper.

Overcoming the Regulatory Bottleneck via Agent-to-Agent Protocols: A Nuclear Case Study Integrating LLMs for Explainable Fault Diagnosis in Complex Systems

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:07:17.583849Z

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=pdf_text observed=2026-06-27T21:42:26.151696Z digest=sha256:726d22a77f0b188586c87859e85c4334dd0e96e3adad4b32eab3d3f9c2e7b1d7