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Paper Citation Record · LEDGER

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation

As of 10 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2505.17579.

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

pith.paper-citation-record.v1
2505.17579 v3

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:49:48.767310Z

measured 15 of 15 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

15 of 15 outbound references displayed

  • verified exact1
  • verified fuzzy5
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92a9d4d8-bc2a-4630-8874-99076aca200f · outbound

This paper cites Deep Intellectual Property Protection: A Survey.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Deep Intellectual Property Protection: A Survey

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:47.596326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:47.596326Z digest=sha256:735a0343d457d35c5b9fbb48636218d3d7916179245b9d2a8f8ac86c0c9818e2

Observation 6fd12706-7b0e-456c-b913-3035a14c5d8e · outbound

This paper cites Adversarial examples in the physical world.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Adversarial examples in the physical world

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:47.707265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:47.707265Z digest=sha256:429c4ebf0f24d662958da42d5bb11f2e7607c1ffe2ef7c77618b5810d0b00b0d

Observation 01caabd8-225a-4e77-9850-26f5b313a41f · outbound

This paper cites Customized Watermarking for Deep Neural Networks via Label Distribution Perturbation.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Customized Watermarking for Deep Neural Networks via Label Distribution Perturbation

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:49:49.078445Z

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=2026-08-07T14:49:47.790079Z digest=sha256:a194bdbc0ace62d83132371ad187449b82325415216889d7c72a505907537b23

Observation 4ff63cf6-297a-4007-bdc0-3f69813e07c1 · outbound

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

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Turning your weakness into a strength: Watermarking deep neural networks by backdooring,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:50.163826Z

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=2026-08-07T14:49:47.899982Z digest=sha256:17874d01dd16bbedf6db164ff3d9a351a24e6e28b8f3d158c459102bf57442ac

Observation 6ef72ba0-d42a-47d5-82ba-db22dce64420 · outbound

This paper cites AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:47.975982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:47.975982Z digest=sha256:ed4fe46aa65be0c8dc6c94550de3a58683994f1095f0a33ff747939b33912c6a

Observation 31f05c83-a9b5-4f5b-97d8-5fd97f02afac · outbound

This paper cites SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:48.056361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:48.056361Z digest=sha256:8f3f2a555aea3900fa77eb290380250109874278d3794e898b2fd513515ba680

Observation 5f1e14f7-a77a-4e3e-af38-d40ce50294c2 · outbound

This paper cites IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:48.145267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:48.145267Z digest=sha256:a14dcc2f246576400226340ae16f26a0854126456d54c37b760e8fc188a2cfd6

Observation 5c4dadde-51c4-4e42-b275-30a1f844a2cd · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Explaining and Harnessing Adversarial Examples

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:48.240706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:48.240706Z digest=sha256:690525068a37a8fe641462b36fe59e90dc9d48fb444cea82d8ad36f17371130e

Observation 7d8f2a72-b4c2-40fd-a5b1-dfffd21511d2 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Imagenet: A large-scale hierarchical image database,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:49.974792Z

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=2026-08-07T14:49:48.323491Z digest=sha256:a7ebc9420bcfe897a8a5d8b1cc48123d310549e6191a6849fb96cac50147ea1f

Observation ac6b6620-32a0-4d65-859a-a5b05000009b · outbound

This paper cites Deep residual learning for image recognition,.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Deep residual learning for image recognition,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:48.412336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:48.412336Z digest=sha256:985bd8afaef91d81e93f0b41aab3ca4954f2f9058097d8cb53e4f5358f866d53

Observation 043e974b-9e07-4088-b90a-98ace881b77e · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Pytorch: An imperative style, high-performance deep learning library,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:49.819612Z

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=2026-08-07T14:49:48.477252Z digest=sha256:de367ad5f1fd38bd339eb7bf59303818f5cf5cc4db0cf05dab84929d0360b487

Observation 571b673c-05e6-4070-a9ca-3d4bfdcd83d8 · outbound

This paper cites Image quality assessment: From error visibility to structural similarity,.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Image quality assessment: From error visibility to structural similarity,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:49.692500Z

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=2026-08-07T14:49:48.583138Z digest=sha256:859ad5842426569579d7aec84a02c5b6d2e298c7be2725020f7543b574d58578

Observation 58ed454f-22e5-4624-aed4-baa53c1a9787 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:48.692444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:48.692444Z digest=sha256:6cb007c22ca7648e8f952ed7e6cd400259dd7b3110592136697b07992bcf8538

Observation 5e122db0-c38a-414f-a253-0fdda2d7a59d · outbound

This paper cites ADV oIP: Adver- sarial detection of encrypted and concealed voip,.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation ADV oIP: Adver- sarial detection of encrypted and concealed voip,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:49:49.526734Z

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=2026-08-07T14:49:48.767310Z digest=sha256:cbb9111e86fb2dc0645bf3e38570fc41155a4ac8c71a6fa39d04f53f0f69d7da

Observation 8e14c429-f86b-48d2-ab0e-3b9477076ef2 · outbound

This paper cites A survey of deep neural network watermarking techniques.

Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation A survey of deep neural network watermarking techniques

Reference 2021

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:49:49.343823Z

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=2026-08-07T14:49:47.525966Z digest=sha256:e98a826a6084b51112ff14c0873eb35a2c1bc50a4764a1070e53a3c7e510a772

Pith citing papers

No inbound Pith citation observations are available.