Paper Citation Record · LEDGER

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model

As of 22 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2412.03539.

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

pith.paper-citation-record.v1
2412.03539 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:22:29.921417Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

45 of 45 outbound references displayed

verified exact1
verified fuzzy6
unresolved29
parse uncertain0
malformed identifier9
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 55262d68-e9ee-4a98-afa3-c48c35903189 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c16375c5-ffaf-4bc6-8a9e-87a3e3524999 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5bfd1eb-2857-4ceb-a735-c9d27f2fcc82 · outbound

This paper cites Biggio, F.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Biggio, F

Reference 3

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Source-reported events for the cited work

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Observation ba429bf0-4889-4853-9b10-605e2fa92bbf · outbound

This paper cites Akhtar, A.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Akhtar, A

Reference 4

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Source-reported events for the cited work

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Observation b0bd428d-eca4-441c-a077-9548b2355128 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 5

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Source-reported events for the cited work

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Observation 5bf44e57-7be7-439b-876a-13aed81f7d12 · outbound

This paper cites Nguyen, S.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Nguyen, S

Reference 6

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Source-reported events for the cited work

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Observation e43960b7-020c-4d64-b50e-d4a8436e8ec7 · outbound

This paper cites Xiong, H.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Xiong, H

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T22:22:29.757776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62823ddb-fd60-4aa1-b18f-6f70223ea115 · outbound

This paper cites Abdel-Basset, A.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Abdel-Basset, A

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T22:22:29.761395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a7aa788-7b78-450c-b12c-ac58aa047cc5 · outbound

This paper cites Szegedy, V.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Szegedy, V

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ebe7173-8036-4ddb-9a95-c132caa50ad1 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Explaining and Harnessing Adversarial Examples

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b21a9a32-6762-432c-9d96-e29a7ed1f636 · outbound

This paper cites Kurakin, I.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Kurakin, I

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:22:31.117160Z

Source-reported events for the cited work

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Observation 45c5610a-7a7b-4049-b8a1-e33d0204b7e5 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 12

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Source-reported events for the cited work

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Observation b19bccc9-54d0-4006-a025-24cd0ea2a2c4 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 13

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Source-reported events for the cited work

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Observation 57c1a1e5-816d-46ec-8dbd-108ab6cdcca2 · outbound

This paper cites Jandial, P.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Jandial, P

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:22:31.092946Z

Source-reported events for the cited work

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Observation a9dbabf2-240f-46dc-9177-648040afd235 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 443850d4-6288-44dd-8344-5a6ffb9bfc76 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation 157225b6-2294-4ad8-b00c-9077059f9323 · outbound

This paper cites AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models

Reference 17

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Source-reported events for the cited work

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Observation 4432bdaa-3306-4e00-8b1c-da7dee9f9c50 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 10d2f136-f0d9-413c-ba8b-eb1c23e70a37 · outbound

This paper cites Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17669d13-be42-497b-99e5-e7b814bd33ee · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 20

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Source-reported events for the cited work

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Observation cda51197-0ef4-4167-8e11-2f0eeb410d1f · outbound

This paper cites Neural Ordinary Differential Equations.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Neural Ordinary Differential Equations

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef719fbd-16cb-4852-8b8a-f827c821e415 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 22

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Source-reported events for the cited work

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Observation 3b66ee42-b4fe-45c5-a4a3-47cb4a9895d4 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 23

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Source-reported events for the cited work

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Observation 1e76febe-7fad-4598-b3cc-24233a7945ec · outbound

This paper cites Intriguing properties of neural networks.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Intriguing properties of neural networks

Reference 24

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Source-reported events for the cited work

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Observation 905cbf81-dc27-4660-9e69-5944ceaaac11 · outbound

This paper cites Carlini, D.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Carlini, D

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c0806e9-5564-476b-b536-87b980f5f605 · outbound

This paper cites Papernot, P.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Papernot, P

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc6840ca-fe24-447b-a855-b15c6e1959d8 · outbound

This paper cites Eykholt, I.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Eykholt, I

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:22:31.054896Z

Source-reported events for the cited work

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Observation 08782635-2c93-413f-99d8-9a64f32945d8 · outbound

This paper cites Goodfellow, J.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Goodfellow, J

Reference 28

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Source-reported events for the cited work

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Observation ae9fc8a8-010f-403c-b6b1-8c8a80f9d18f · outbound

This paper cites Ledig, L.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Ledig, L

Reference 29

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Source-reported events for the cited work

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Observation b1f6ab9c-6751-4d50-b6c0-72304e428e0c · outbound

This paper cites A Comprehensive Survey on Data-Efficient GANs in Image Generation.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model A Comprehensive Survey on Data-Efficient GANs in Image Generation

Reference 30

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Source-reported events for the cited work

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Observation bee93ae6-2706-4641-b6f4-ed626511eb17 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52e6d696-fa87-486c-ad6b-716f9f043bf2 · outbound

This paper cites Isola, J.-Y.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Isola, J.-Y

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4625dca8-8882-4ffe-9848-34a0d1a9762d · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 33

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Observation 8c7bf208-b66b-4ac7-9a93-cceaf1aa10ae · outbound

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NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 34

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Source-reported events for the cited work

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This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 35

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Observation 8c369432-d954-4f76-98d3-bdaccc74494c · outbound

This paper cites Krizhevsky, G.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Krizhevsky, G

Reference 36

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Observation 70ed78a0-c6c5-4f5f-b42e-16fb1135e329 · outbound

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

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 37

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Source-reported events for the cited work

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Observation c82bf759-daa4-424c-9696-397b424addea · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 38

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Observation f52b4fb9-4db4-435d-99c4-4136fc48ef1a · outbound

This paper cites Huang, Z.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Huang, Z

Reference 39

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Source-reported events for the cited work

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Observation 9f4a25be-3baf-4b37-9ed8-3275050c3bec · outbound

This paper cites Adversarial Machine Learning at Scale.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Adversarial Machine Learning at Scale

Reference 40

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Source-reported events for the cited work

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Observation 62faff73-a6ed-4a6f-b7e6-a1ff6b194fb9 · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 41

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Observation 921c1a04-c9bc-4188-8310-289699d4581f · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 42

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Source-reported events for the cited work

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Observation c171bfe7-cd47-43a1-868e-32e80c9bb4bb · outbound

This paper cites Singh, Piqa: Physical interaction: Question answering, accessed: 2024-10-17 (2020).

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Singh, Piqa: Physical interaction: Question answering, accessed: 2024-10-17 (2020)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:22:31.010411Z

Source-reported events for the cited work

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Observation 8a7dd34b-6939-4081-968e-374e4efc6c44 · outbound

This paper cites Paszke, S.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Paszke, S

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:22:30.996236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3200e2bb-96b4-4158-b011-1f040c54a0de · outbound

This paper cites an unresolved cited work.

NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model Unresolved cited work

Reference 45

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.