Paper Citation Record · LEDGER

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis

As of 23 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2412.14492.

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

pith.paper-citation-record.v1
2412.14492 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:14:07.112039Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact5
verified fuzzy2
unresolved6
parse uncertain0
malformed identifier2
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4faa7a77-65ee-41b1-a4bc-568c37e75781 · outbound

This paper cites Process Safety and Environmental Protection 165, 463–474.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Process Safety and Environmental Protection 165, 463–474

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T12:14:07.860529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f842390c-275e-4d30-843e-e1590dc2a140 · outbound

This paper cites bioRxiv , 2024–10.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis bioRxiv , 2024–10

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:07.830888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f929510a-e299-4090-9d0d-ab9d1208e6c1 · outbound

This paper cites Pro- ceedings of the National Academy of Sciences of the United States of Amer- ica 116, 22071–22080.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Pro- ceedings of the National Academy of Sciences of the United States of Amer- ica 116, 22071–22080

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:07.036250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f182543d-1762-4fe9-b32d-09f849062692 · outbound

This paper cites OpenAI, 2024a.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis OpenAI, 2024a

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:14:07.808416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7f4edbe4-2dfa-4442-99b5-d8414ffe92a6 · outbound

This paper cites Nature Machine Intelligence 2023 , 1–11URL: https://www.nature.com/articles/s42256-023-00692-8 , doi:10.1038/s42256-023-00692-8.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Nature Machine Intelligence 2023 , 1–11URL: https://www.nature.com/articles/s42256-023-00692-8 , doi:10.1038/s42256-023-00692-8

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:07.096366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d242da5-c6fa-4296-a75a-f7c074e7eaf8 · outbound

This paper cites AIChE Journal 63, 4329–4342.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis AIChE Journal 63, 4329–4342

Reference 16

Resolution: verified exact; doi, observed 2026-08-11T12:14:07.172928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dcbd5085-38c8-404a-a99c-8aff9b2dd2d3 · outbound

This paper cites Chen, H., Constante-Flores, G.E., Li, C.,.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Chen, H., Constante-Flores, G.E., Li, C.,

Reference 17

Resolution: verified exact; doi, observed 2026-08-11T12:14:07.346873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ac8fc6d2-d03c-4cc5-9ab5-fafba2991689 · outbound

This paper cites International Journal of Man- Machine Studies 27, 221–234.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis International Journal of Man- Machine Studies 27, 221–234

Reference 1987

Resolution: verified exact; doi, observed 2026-08-11T12:14:07.265469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 21ab5458-6fc8-41af-9b91-fec785069099 · outbound

This paper cites Computers & Chemical Engineering 21, S655–S660.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Computers & Chemical Engineering 21, S655–S660

Reference 1997

Resolution: verified exact; doi, observed 2026-08-11T12:14:07.200504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4314d9ee-5d75-4d9f-acf4-662ead37addf · outbound

This paper cites IEEE Transactions on control systems technology 16, 799–808.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis IEEE Transactions on control systems technology 16, 799–808

Reference 2008

Resolution: verified exact; doi, observed 2026-08-11T12:14:07.312843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3cf7076b-1b0f-4bc8-a3fc-68fa74c1266e · outbound

This paper cites an unresolved cited work.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Unresolved cited work

Reference 2016

Resolution: malformed identifier; no resolver link, observed 2026-08-11T12:14:07.077526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c45e881-e059-4013-b136-7b0debdb22c0 · outbound

This paper cites URL: https://doi.org/10.7910/DVN/6C3JR1, doi:10.7910/DVN/ 6C3JR1.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis URL: https://doi.org/10.7910/DVN/6C3JR1, doi:10.7910/DVN/ 6C3JR1

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:07.087087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b55c33c2-8601-4c2d-aaa9-5ef38c1dda9b · outbound

This paper cites an unresolved cited work.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Unresolved cited work

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:07.023554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7bb60e8-e938-4656-b910-d8fa8a6fb591 · outbound

This paper cites Computers & Chemical Engineering 157, 107619.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Computers & Chemical Engineering 157, 107619

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:06.973580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41d389b4-4e59-49f0-abb6-8fd775f2b63a · outbound

This paper cites LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T12:14:07.000442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c61abf9b-4549-4531-8f13-b475f5992931 · outbound

This paper cites Graph-to-SFILES: Control structure prediction from process topologies using generative artificial intelligence.

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis Graph-to-SFILES: Control structure prediction from process topologies using generative artificial intelligence

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T12:14:07.767056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.