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Paper Citation Record · LEDGER

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2509.00027.

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

pith.paper-citation-record.v1
2509.00027 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:32:30.171516Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

32 of 32 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2aaa4970-cc80-4ae5-b873-804ccadd2b88 · outbound

This paper cites Procedia Computer Science225, 1302–1311 (2023).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Procedia Computer Science225, 1302–1311 (2023)

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 9592a1c5-089b-4396-82bb-7ad59ccce6a9 · outbound

This paper cites Nature Machine Intelligence 2(6), 305–311 (2020).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Nature Machine Intelligence 2(6), 305–311 (2020)

Reference 2

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raw_fallback, observed 2026-08-05T18:32:34.074020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 29b4d257-2913-4865-8649-5dad311c87e8 · outbound

This paper cites Hidden Data Privacy Breaches in Federated Learning.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Hidden Data Privacy Breaches in Federated Learning

Reference 3

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local_arxiv, observed 2026-08-05T18:32:30.850850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e1f96b39-3e29-4f1b-8921-def5e57aaa4e · outbound

This paper cites Evaluation of Inference Attack Models for Deep Learning on Medical Data.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Evaluation of Inference Attack Models for Deep Learning on Medical Data

Reference 4

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no resolver link, observed 2026-08-05T18:32:27.729394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 480ab126-73bc-43b7-a1f5-24d6afc005f0 · outbound

This paper cites In: International Conference on Neural Information Processing.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: International Conference on Neural Information Processing

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 05006800-12fc-4e9a-9eb2-cd6635ef4c59 · outbound

This paper cites In: 2023 IEEE 36th Computer Security Foundations Symposium (CSF).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: 2023 IEEE 36th Computer Security Foundations Symposium (CSF)

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 77dfdb27-6dff-470b-88fe-8581e69ae476 · outbound

This paper cites arXiv preprint arXiv:2411.14516 (2024).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning arXiv preprint arXiv:2411.14516 (2024)

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 24aa1763-2c51-4b34-be3a-47edb84f67d3 · outbound

This paper cites In: 2018 IEEE 31st computer security foundations symposium (CSF).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: 2018 IEEE 31st computer security foundations symposium (CSF)

Reference 8

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raw_fallback, observed 2026-08-05T18:32:33.256054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T18:32:28.204730Z digest=sha256:8ba4771ce4d34d15dd45499e72785af35a2ea8371d4f3c4e3668dc480b006b21

Observation 2c0994d5-cef1-406e-b3cc-3e6d1d3761f8 · outbound

This paper cites Transpose Attack: Stealing Datasets with Bidirectional Training.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Transpose Attack: Stealing Datasets with Bidirectional Training

Reference 9

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local_arxiv, observed 2026-08-05T18:32:30.386695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 03e54c5b-f622-4f7d-9201-ce5083e51e77 · outbound

This paper cites an unresolved cited work.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ab442e85-2490-41e2-83e6-a35a86aca383 · outbound

This paper cites In: 32nd USENIX Security Symposium (USENIX Security 23).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: 32nd USENIX Security Symposium (USENIX Security 23)

Reference 11

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raw_fallback, observed 2026-08-05T18:32:32.952321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T18:32:28.508149Z digest=sha256:6841db66959519019019cd3134085272f407d34af0a7cf152e6ef135c7975cba

Observation e851d372-51d0-4639-a392-27793bbf28de · outbound

This paper cites an unresolved cited work.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T18:32:28.619746Z digest=sha256:924a4b6ba783d4a763842d7f50f3f6ecb8d23b077caa9c4e74f59b00a02a716a

Observation be94aa9a-9c28-4f10-bf02-dc23a8fa0b8f · outbound

This paper cites Medical and Bi- ological Engineering and Computing44, 619–631 (2006).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Medical and Bi- ological Engineering and Computing44, 619–631 (2006)

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1f1cf594-bfae-46fa-bd4e-8eefaa7d6f95 · outbound

This paper cites In: International symposium on research in attacks, intrusions, and defenses.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: International symposium on research in attacks, intrusions, and defenses

Reference 14

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raw_fallback, observed 2026-08-05T18:32:32.681527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1aed96b9-cef9-4016-a618-5aeb0c4fe7b3 · outbound

This paper cites Fine-Tuning Is All You Need to Mitigate Backdoor Attacks.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Fine-Tuning Is All You Need to Mitigate Backdoor Attacks

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f1142d3d-e14b-42de-9ffc-ef49e8b1f03e · outbound

This paper cites In: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fdbe6673-527d-4ff8-972a-7e37a846a8b9 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 17

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raw_fallback, observed 2026-08-05T18:32:32.326628Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4b23b01a-c747-4cce-994a-eb26830bbdd8 · outbound

This paper cites In: ICLR2018 Conference (2018).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: ICLR2018 Conference (2018)

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fd24d44b-6595-48d5-b3df-0f9a1856a45d · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21)

Reference 19

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raw_fallback, observed 2026-08-05T18:32:32.039194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 4f65e6a5-6f37-4eb1-8761-ff15c95fb0fe · outbound

This paper cites CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet

Reference 20

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Unavailable: canonical work link unavailable.

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Observation f41d68f7-69e9-410e-ad64-d17f03f161a2 · outbound

This paper cites In: International Conference on Learning Representations (ICLR) (2019).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: International Conference on Learning Representations (ICLR) (2019)

Reference 21

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Unavailable: canonical work link unavailable.

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Observation 70fa956d-ac73-4062-a816-b8089059ef97 · outbound

This paper cites In: IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: IEEE 18th International Symposium on Biomedical Imaging (ISBI)

Reference 22

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raw_fallback, observed 2026-08-05T18:32:31.913214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 71a6de30-2fbb-4ec5-8ff9-f8797bd856eb · outbound

This paper cites Scientific data p.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Scientific data p

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 75f405d9-c463-4f0e-8c14-b464264fec76 · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 8517196b-44f7-4350-b10e-c576167d8be8 · outbound

This paper cites an unresolved cited work.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Unresolved cited work

Reference 25

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no resolver link, observed 2026-08-05T18:32:29.749170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 35218eb3-b413-41d2-880f-e2202d65a5b2 · outbound

This paper cites Scientific Data 10(1), 41 (2023) Mitigating Data Exfiltration via Layer-Wise LR Decay FT 11.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Scientific Data 10(1), 41 (2023) Mitigating Data Exfiltration via Layer-Wise LR Decay FT 11

Reference 26

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raw_fallback, observed 2026-08-05T18:32:31.598953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6cf71953-d1e4-4947-b6b0-5d1ecebc388c · outbound

This paper cites In: CVPR.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: CVPR

Reference 27

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raw_fallback, observed 2026-08-05T18:32:31.469712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c7f90a0b-2d67-4484-b65a-5cead7316ee8 · outbound

This paper cites MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7cfd2a00-b95c-4739-8178-7d32c133cd3f · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 29

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raw_fallback, observed 2026-08-05T18:32:31.294246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ec82eebf-55de-4566-be8a-4c667027a49d · outbound

This paper cites an unresolved cited work.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning Unresolved cited work

Reference 30

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raw_fallback, observed 2026-08-05T18:32:31.170896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation be7e0222-274a-4647-95b6-18605e4d7915 · outbound

This paper cites IEEE Transactions on Image Process- ing 13(4), 600–612 (2004).

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning IEEE Transactions on Image Process- ing 13(4), 600–612 (2004)

Reference 31

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raw_fallback, observed 2026-08-05T18:32:31.036008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 0a42fcfb-66ad-4d72-9ebf-701e5908f830 · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 32

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no resolver link, observed 2026-08-05T18:32:30.171516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.