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Paper Citation Record · LEDGER

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems

As of 6 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2603.25749.

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

pith.paper-citation-record.v1
2603.25749 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T10:54:05.436866Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

19 of 19 outbound references displayed

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  • unresolved0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 15b5da83-7473-45db-a339-72c61ca96e57 · outbound

This paper cites Implementation of a grid-integrated pv-battery system for residential and electrical vehicle applications.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Implementation of a grid-integrated pv-battery system for residential and electrical vehicle applications

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 3f7f28c2-dfb2-442f-9a2f-99812d60392b · outbound

This paper cites World energy outlook 2024.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems World energy outlook 2024

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 6e587c33-cbfd-46ad-8e16-1cb089083543 · outbound

This paper cites The detection of series arc fault in photovoltaic systems based on the arc current entropy.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems The detection of series arc fault in photovoltaic systems based on the arc current entropy

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation c7ee3506-f88a-4eb0-9b48-fecaca9fc236 · outbound

This paper cites Real-time dc series arc fault detection based on noise pattern analysis in photovoltaic system.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Real-time dc series arc fault detection based on noise pattern analysis in photovoltaic system

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 6df0b582-9b82-415a-acb2-2a15befa93cb · outbound

This paper cites Detecting and localizing series arc fault in photovoltaic systems based on time and frequency characteristics of capacitor current.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Detecting and localizing series arc fault in photovoltaic systems based on time and frequency characteristics of capacitor current

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation a38b8d25-9a0c-4894-85e9-498b92b80d06 · outbound

This paper cites DC series arc fault detector with differential dwt and variable threshold method for photovoltaic systems.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems DC series arc fault detector with differential dwt and variable threshold method for photovoltaic systems

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T10:54:05.436866Z digest=sha256:8668606c82ca6ed62af44f5dbe06923d47d62fca72147834f3ed82dae706c4a0

Observation a0661943-03e8-4803-8e6b-5ad633ca6556 · outbound

This paper cites PV arc fault circuit interrupter with knowledge distillation-based lightweight convolutional neural network and sscb integration.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems PV arc fault circuit interrupter with knowledge distillation-based lightweight convolutional neural network and sscb integration

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation e15bd33e-5b28-4df5-bc25-a6c22de9bba7 · outbound

This paper cites A series arc fault detection method based on time-frequency markov permutation transition field for photovoltaic systems with power electronic devices.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems A series arc fault detection method based on time-frequency markov permutation transition field for photovoltaic systems with power electronic devices

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T10:54:05.436866Z digest=sha256:c17d82d6b6206f5cca904aab0d935f9a061c8e800532bc17e99c0f00077b7c7c

Observation 0f1c634b-f709-413c-bad1-90470cb2d0f6 · outbound

This paper cites Photovoltaic system DC series arc fault: A case study.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Photovoltaic system DC series arc fault: A case study

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation dd693349-ff20-403b-bc93-1bb400be08f2 · outbound

This paper cites Isolation and detection of arc fault noise in a real PV system using current demodulation and autocorrelation coefficients.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Isolation and detection of arc fault noise in a real PV system using current demodulation and autocorrelation coefficients

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 12b7b38c-7a1a-44e9-9158-5376d157cf0d · outbound

This paper cites EMI effects of power converters.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems EMI effects of power converters

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 0dbd0e5c-7200-4caa-aefa-c9e32e017914 · outbound

This paper cites Domain-adversarial training of neural networks.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Domain-adversarial training of neural networks

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T10:54:05.436866Z digest=sha256:e214bd5bc51b30aa4531e8429bcaa611a7fcc39d3c1562ba5dcc05e8ef98c22b

Observation f4e24652-dc49-435d-8dd2-c5344d7df951 · outbound

This paper cites Invariant risk minimization is a total vari- ation model.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Invariant risk minimization is a total vari- ation model

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T10:55:29.076941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T10:54:05.436866Z digest=sha256:80484dddf73608d0eabe5ef8f2dec39277019d9eb42d81bbee2ae1c17fee0d1a

Observation e78c30b1-3a69-43d1-8dbe-64b628f3caaf · outbound

This paper cites Invariant risk minimization games.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Invariant risk minimization games

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-15T10:54:05.436866Z digest=sha256:bc31228956060f387f21627d93cc0c9276d0214b0114725a99e4855b538e53cd

Observation 10a8e263-8155-4e0e-8ff3-ea79c21d86c1 · outbound

This paper cites Bridging theory and algo- rithm for domain adaptation.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Bridging theory and algo- rithm for domain adaptation

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation dcaf8e8f-9352-4ef7-98ac-63437a01438b · outbound

This paper cites Photovoltaic degradation rates—an analytical review.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Photovoltaic degradation rates—an analytical review

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 3c567b56-dd9e-4891-9a23-50f61801b2cb · outbound

This paper cites International col- laboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems International col- laboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation e2722ee5-bd4c-426d-99fb-8e8032666c5c · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems Overcoming catastrophic forgetting in neural networks

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T10:55:29.070460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 3a82ad08-fb0b-4177-bd61-be1efba10fd7 · outbound

This paper cites (2025) Arc fault detection using embedded ai models application note, rev 1.0.

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems (2025) Arc fault detection using embedded ai models application note, rev 1.0

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T10:55:29.068330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Pith citing papers

No inbound Pith citation observations are available.