Paper Citation Record · LEDGER

Towards the Resistance of Neural Network Watermarking to Fine-tuning

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2505.01007.

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

pith.paper-citation-record.v1
2505.01007 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:36:26.039400Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T12:20:41.291944Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T12:21:21.233481Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy12
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06a2d160-e701-4baa-9f28-2bccda6c5f32 · outbound

This paper cites Turning your weakness into a strength: Watermarking deep neural networks by backdooring.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Turning your weakness into a strength: Watermarking deep neural networks by backdooring

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.917585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d95d35d9-2fd4-47a6-be23-36488e6a5c7a · outbound

This paper cites Neural network laundering: Removing black-box backdoor watermarks from deep neural networks.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Neural network laundering: Removing black-box backdoor watermarks from deep neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.407928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 44312f7d-e45e-42fd-9fc3-e9943a6e2645 · outbound

This paper cites Certified neural network watermarks with randomized smoothing.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Certified neural network watermarks with randomized smoothing

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.391977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5031bf0f-b436-4132-8b4e-9f0180739d39 · outbound

This paper cites One-shot learning of object categories.

Towards the Resistance of Neural Network Watermarking to Fine-tuning One-shot learning of object categories

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.375348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 15046766-65aa-47de-973e-5b482861c45d · outbound

This paper cites Functional invariants to watermark large transformers.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Functional invariants to watermark large transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.941059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e8090b0-861c-417f-88c5-0c5ee6ab165d · outbound

This paper cites Deep residual learning for image recognition.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Deep residual learning for image recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.946075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c04c02-6ee1-427d-a598-dbb06d43816b · outbound

This paper cites Fundamentals of digital image processing.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Fundamentals of digital image processing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.336775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b84d7a70-1c74-4866-96b1-945da41b2a02 · outbound

This paper cites A watermark for large language models.

Towards the Resistance of Neural Network Watermarking to Fine-tuning A watermark for large language models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.957053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed651bbf-7581-45d4-af55-b261c80a158c · outbound

This paper cites Similarity of neural network representations revisited.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Similarity of neural network representations revisited

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.309974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a79498f4-ad1c-450f-b34d-8a16629cbfb7 · outbound

This paper cites The Complex Gradient Operator and the CR-Calculus.

Towards the Resistance of Neural Network Watermarking to Fine-tuning The Complex Gradient Operator and the CR-Calculus

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.967926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee7b0e53-693b-4d7f-89d9-af4a2911f5fb · outbound

This paper cites Learning multiple layers of features from tiny images.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Learning multiple layers of features from tiny images

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.973619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aea1929a-9892-4b31-842a-9829f06b2571 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Imagenet classification with deep convolutional neural networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.978505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf0748b-95d5-49da-902d-7005d1b10829 · outbound

This paper cites Watermarking deep neural networks with greedy residuals.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Watermarking deep neural networks with greedy residuals

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:25.984320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25177505-fe24-4a1f-a133-81a4a6ff87c8 · outbound

This paper cites Deep neural network fingerprinting by conferrable adversarial examples.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Deep neural network fingerprinting by conferrable adversarial examples

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.260187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 87b95d4c-e8b0-4134-adcf-66d7a595c332 · outbound

This paper cites Digital watermarking.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Digital watermarking

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.242701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6c683702-1213-43f2-8249-28c12bb58a9f · outbound

This paper cites Dimension-independent certified neural network watermarks via mollifier smoothing.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Dimension-independent certified neural network watermarks via mollifier smoothing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.225272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9bb688b1-63d4-427b-9a92-7e2b6e788e3d · outbound

This paper cites On the robustness of backdoor-based watermarking in deep neural networks.

Towards the Resistance of Neural Network Watermarking to Fine-tuning On the robustness of backdoor-based watermarking in deep neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.208141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b98cbb67-98fa-4e42-a74a-3b10b92ad9da · outbound

This paper cites Deep neural network watermarking against model extraction attack.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Deep neural network watermarking against model extraction attack

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.190913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2b889da6-9330-47ff-b220-7b4e8a3b56a9 · outbound

This paper cites Defects of convolutional decoder networks in frequency representation.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Defects of convolutional decoder networks in frequency representation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.173093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 12f2c8ea-ece0-40ca-a306-9dda472e44b7 · outbound

This paper cites Embedding watermarks into deep neural networks.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Embedding watermarks into deep neural networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:26.019241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 207c13e3-4983-4357-aeb7-acdd5bf3707e · outbound

This paper cites Watermarking in deep neural networks via error back-propagation.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Watermarking in deep neural networks via error back-propagation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:36:26.145189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2f5c1141-88bf-4c85-8f1a-3c625aeb0a79 · outbound

This paper cites Instructional Fingerprinting of Large Language Models.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Instructional Fingerprinting of Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:26.029471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 912fff5a-a2ee-4496-8f5e-2905a9cbfefb · outbound

This paper cites Huref: Human-readable fingerprint for large language models.

Towards the Resistance of Neural Network Watermarking to Fine-tuning Huref: Human-readable fingerprint for large language models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:26.034680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92f8e7b5-4432-4920-8de7-63d9e5ad5aaa · outbound

This paper cites REEF: Representation Encoding Fingerprints for Large Language Models.

Towards the Resistance of Neural Network Watermarking to Fine-tuning REEF: Representation Encoding Fingerprints for Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:26.039400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ca12684f-2fdb-4ace-8971-bc22f2df64ed · inbound

LLM DNA: Tracing Model Evolution via Functional Representations cites this paper.

LLM DNA: Tracing Model Evolution via Functional Representations Towards the Resistance of Neural Network Watermarking to Fine-tuning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:21:21.236731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.