Paper Citation Record · LEDGER

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things

As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2506.01450.

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

pith.paper-citation-record.v1
2506.01450 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:03.541122Z

measured 30 of 30 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 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

30 of 30 outbound references displayed

verified exact13
verified fuzzy1
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69ac2b31-439a-44b7-91a3-6593aebb6106 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:57.337676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d15093a4-6afa-4374-b394-1309dab47d4e · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:52:06.571963Z

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.

Observation 90cc4a13-6ebf-4520-8981-cba7b2590647 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 3

Resolution: verified exact; doi, observed 2026-08-07T11:52:05.233054Z

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.

Observation 19d6486e-fcff-438c-9290-b09049832d59 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 4

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:52:06.442457Z

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.

Observation a5a7449c-fbd1-434f-b157-1fa488a34777 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 5

Resolution: verified exact; doi, observed 2026-08-07T11:52:05.145786Z

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.

Observation 9d683094-2701-4c81-82cd-83ce9ff33013 · outbound

This paper cites Molnar, Interpretable Machine Learning, 3rd Edition, 2025.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Molnar, Interpretable Machine Learning, 3rd Edition, 2025

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:52:06.734858Z

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.

Observation 362cfbd1-6a4f-44b3-a655-733ffdeda560 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:59.894254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6c51a7c-edb3-4245-8373-c256b201d1a8 · outbound

This paper cites Learning Important Features Through Propagating Activation Differences.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Learning Important Features Through Propagating Activation Differences

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:00.299995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c37889f-5f66-4a24-aa9b-22f1c9d6f6ef · outbound

This paper cites A Multilinear Sampling Algorithm to Estimate Shapley Values.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things A Multilinear Sampling Algorithm to Estimate Shapley Values

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:52:04.983328Z

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.

Observation 72ef1e3b-34ff-4f25-a29c-a47096f75e58 · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things A Unified Approach to Interpreting Model Predictions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:01.555087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c996113-d6c6-4c27-b20f-f490cf6e6aa0 · outbound

This paper cites Explaining individual predictions when features are dependent: More accurate approximations to Shapley values.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Explaining individual predictions when features are dependent: More accurate approximations to Shapley values

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:52:04.806132Z

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.

Observation 3a163827-6560-4e45-939d-74d2fc75ae66 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:01.962514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f338792e-3fa6-4c91-bdcf-c30047e1c262 · outbound

This paper cites FastSHAP: Real-Time Shapley Value Estimation.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things FastSHAP: Real-Time Shapley Value Estimation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.055029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee42cea7-37ce-4b07-9455-9ce413ccb820 · outbound

This paper cites Simon, T.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Simon, T

Reference 14

Resolution: verified exact; doi, observed 2026-08-07T11:52:04.542693Z

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.

Observation ddc49398-d2fd-4e72-be08-f2d7e50b1de6 · outbound

This paper cites Bounding the Estimation Error of Sampling-based Shapley Value Approximation.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Bounding the Estimation Error of Sampling-based Shapley Value Approximation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.245104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e783e80c-75e1-421f-9236-64b698da5860 · outbound

This paper cites Shapley explainability on the data manifold.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Shapley explainability on the data manifold

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.325185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c7f1c4f-07da-4f9b-a4ce-3ddb1fb5176d · outbound

This paper cites Huang, Y.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Huang, Y

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.401186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45fb6b97-61ff-432d-8d2f-c7deb354fd0b · outbound

This paper cites An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:52:04.328111Z

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.

Observation 0d0d9437-00cc-4947-84c3-05e372f05338 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.554478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff581c0f-a9c1-44e3-849c-f69670b0782e · outbound

This paper cites Brusa, L.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Brusa, L

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.666742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c849b67-1686-4d0d-a5d4-40998c6469f6 · outbound

This paper cites Jacob, F.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Jacob, F

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:02.742432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7378576c-34f2-4b47-947d-e028cb524b18 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 22

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:52:06.030522Z

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.

Observation 61bc74e2-58ba-47dd-b455-c4b2203eb2f5 · outbound

This paper cites Mathuros, S.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Mathuros, S

Reference 23

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:52:05.873659Z

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.

Observation 6e065e42-0dd4-4c57-acfb-779056d188f4 · outbound

This paper cites Symp, 2024.doi:10.14722/ndss.2024.23216.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Symp, 2024.doi:10.14722/ndss.2024.23216

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:52:05.695440Z

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.

Observation a0044f34-9bc9-4297-a487-08ffe276682d · outbound

This paper cites Explainable Anomaly Detection for Industrial Control System Cybersecurity.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Explainable Anomaly Detection for Industrial Control System Cybersecurity

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:52:04.142892Z

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.

Observation 480d2903-09fb-4eb6-92ec-6ebd10e1c768 · outbound

This paper cites Hwang, T.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Hwang, T

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:03.128951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4a55d15-5e7a-43b1-ad32-f8e56b59cdaa · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 27

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:52:05.391218Z

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.

Observation 82ebd1ef-1f57-4925-9a8a-274668997e96 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 28

Resolution: verified exact; doi, observed 2026-08-07T11:52:03.965075Z

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.

Observation 71af7462-bc4a-4fe7-8256-151270f1d43e · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:52:06.649508Z

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.

Observation ed878e11-792a-46ea-9ec1-48c24b46ee75 · outbound

This paper cites an unresolved cited work.

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things Unresolved cited work

Reference 30

Resolution: verified exact; doi, observed 2026-08-07T11:52:03.734597Z

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.

Pith citing papers

No inbound Pith citation observations are available.