Paper Citation Record · LEDGER

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks

As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.11168.

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

pith.paper-citation-record.v1
2412.11168 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:21:47.180378Z

measured 37 of 37 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 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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1afaee15-0c91-4e6c-b9a6-ff7d0d96d196 · outbound

This paper cites Intriguing properties of neural networks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Intriguing properties of neural networks,

Reference 1

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Source-reported events for the cited work

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Observation fa4b47e4-4b40-4edc-aa5d-73f392adef36 · outbound

This paper cites Explaining and harnessing adversarial examples,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Explaining and harnessing adversarial examples,

Reference 2

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Observation 1c310578-6e3e-4f67-afac-96f0168fe496 · outbound

This paper cites Adversarial examples: Attacks and defenses for deep learning,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Adversarial examples: Attacks and defenses for deep learning,

Reference 3

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Observation 607f65b8-6c07-4e1c-b196-771d1e11a58d · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Towards deep learning models resistant to adversarial attacks,

Reference 4

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Observation 5b81565e-e397-4245-859f-e36b97dec889 · outbound

This paper cites Boosting adversarial attacks with momentum,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Boosting adversarial attacks with momentum,

Reference 5

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Observation 5e926c17-5f80-4036-a2bb-1f4612f54611 · outbound

This paper cites Multi- layer feature division transferable adversarial attack,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Multi- layer feature division transferable adversarial attack,

Reference 6

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Observation 0233dc8d-31a3-4ef8-85da-f9f32a115d38 · outbound

This paper cites Enhance transferability of adver- sarial examples with model architecture,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Enhance transferability of adver- sarial examples with model architecture,

Reference 7

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Observation 969d570d-fa8e-45af-b232-d45b8d2c8fde · outbound

This paper cites Dynamic generative targeted attacks with pattern injection,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Dynamic generative targeted attacks with pattern injection,

Reference 8

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Observation 240a58cb-b628-489d-8313-042ee18ad985 · outbound

This paper cites Towards evaluating the robustness of neural networks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Towards evaluating the robustness of neural networks,

Reference 9

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Observation 3af39c1f-9e97-4cdc-ab6f-ec527851a2d7 · outbound

This paper cites Towards imperceptible and robust adversarial example attacks against neural networks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Towards imperceptible and robust adversarial example attacks against neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.388182Z

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Observation 1284b92b-808c-4875-a65a-1729e7ef8727 · outbound

This paper cites Towards large yet imperceptible adversarial image perturbations with perceptual color distance,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Towards large yet imperceptible adversarial image perturbations with perceptual color distance,

Reference 11

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Observation b26f0b1c-7b93-4237-baff-a1305495e41b · outbound

This paper cites Perceptual adversarial robustness: Defense against unseen threat models,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Perceptual adversarial robustness: Defense against unseen threat models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.375238Z

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Observation eee2bb62-22b3-47d1-884b-6c2d6dabe4fb · outbound

This paper cites Advdrop: Adversarial attack to dnns by dropping information,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Advdrop: Adversarial attack to dnns by dropping information,

Reference 13

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Observation 9aa18ac2-adee-4fe7-9dd0-5b8bac1c3664 · outbound

This paper cites Exploring fre- quency adversarial attacks for face forgery detection,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Exploring fre- quency adversarial attacks for face forgery detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.362250Z

Source-reported events for the cited work

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Observation 0414a28d-268b-4ff7-8416-5cdee8e5f1ef · outbound

This paper cites Frequency-driven imperceptible adversarial attack on semantic similarity,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Frequency-driven imperceptible adversarial attack on semantic similarity,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.355846Z

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Observation 2a88d44e-9c45-4e2e-b463-24cca2c67a01 · outbound

This paper cites Impercep- tible adversarial attack via invertible neural networks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Impercep- tible adversarial attack via invertible neural networks,

Reference 16

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Observation 06c15ece-8c41-4771-806a-389fc0e7f170 · outbound

This paper cites On the suitability of lp-norms for creating and preventing adversarial examples,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks On the suitability of lp-norms for creating and preventing adversarial examples,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.341664Z

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Observation 0248e79f-9f95-4a2e-b4b9-2ed23de6ab87 · outbound

This paper cites Evading defenses to transferable adversarial examples by translation-invariant attacks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Evading defenses to transferable adversarial examples by translation-invariant attacks,

Reference 18

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Observation d113e3fe-4379-40d9-b4f6-0f3d1f18d695 · outbound

This paper cites Nesterov accelerated gradient and scale invariance for adversarial attacks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Nesterov accelerated gradient and scale invariance for adversarial attacks,

Reference 19

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Observation 6e2a9cf4-17de-498f-bc66-2f78636b251b · outbound

This paper cites On success and simplicity: A second look at transferable targeted attacks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks On success and simplicity: A second look at transferable targeted attacks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.319790Z

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Observation 60e2c429-4f59-4585-a11c-ab99bdfddfe9 · outbound

This paper cites Enhancing the transferability of adversarial attacks through variance tuning,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Enhancing the transferability of adversarial attacks through variance tuning,

Reference 21

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Observation 008d047b-13cf-4e98-a2c9-e764761edf61 · outbound

This paper cites Improving the transferability of adversarial samples by path-augmented method,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Improving the transferability of adversarial samples by path-augmented method,

Reference 22

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Observation 64c6df27-e43c-402c-96e9-441bcdee14f1 · outbound

This paper cites Adam: A method for stochastic optimization,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Adam: A method for stochastic optimization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.298589Z

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Observation b262b21b-663c-42e0-ad42-b001072a0446 · outbound

This paper cites Sgdr: Stochastic gradient descent with warm restarts,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Sgdr: Stochastic gradient descent with warm restarts,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.291883Z

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Observation 0a65012d-ae78-46c4-b1f5-b8135428d0d6 · outbound

This paper cites Decoupled weight decay regularization,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Decoupled weight decay regularization,

Reference 25

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Source-reported events for the cited work

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Observation 0fd98446-37bb-4953-9583-b58096227505 · outbound

This paper cites An overview of gradient descent optimization algorithms.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks An overview of gradient descent optimization algorithms

Reference 26

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Observation 49b233b9-5ace-45da-9653-f357c83975f2 · outbound

This paper cites Early stopping-but when?,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Early stopping-but when?,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.277486Z

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Observation 9bf549e0-b741-4290-b3cd-75435aeec3e0 · outbound

This paper cites Optimized approximation algorithm in neural networks without overfitting,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Optimized approximation algorithm in neural networks without overfitting,

Reference 28

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Observation 3a3b9a35-ca5c-4782-9be5-33e4d0b6e218 · outbound

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PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Understanding and improving early stopping for learning with noisy labels,

Reference 29

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Observation 3494caa0-38ce-4805-a36a-4d9c602334cd · outbound

This paper cites Adversarial attacks and defences competition,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Adversarial attacks and defences competition,

Reference 30

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Source-reported events for the cited work

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Observation 44f45559-a6f2-4774-a420-df33f8be1497 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Imagenet classification with deep convolutional neural networks,

Reference 31

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Source-reported events for the cited work

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Observation e5d7a66f-62f7-4106-911c-4526e13296cd · outbound

This paper cites Deep residual learning for image recognition,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Deep residual learning for image recognition,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.245953Z

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Observation 950e13d6-d3d6-46ad-bbe0-49208113a941 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Very deep convolutional networks for large-scale image recognition,

Reference 33

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Observation e96df687-d67a-4153-be4d-d61ccfb73b7d · outbound

This paper cites Mo- bilenetv2: Inverted residuals and linear bottlenecks,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Mo- bilenetv2: Inverted residuals and linear bottlenecks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.230095Z

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Observation f8afe5ad-2f8b-4934-8672-981e2566fc59 · outbound

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PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Wide residual networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.222748Z

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Observation 3efdbea0-c239-4f58-bf24-99b6d7189454 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 36

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Observation 7979e3d8-5169-45c2-be6c-44ae53bee9da · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks The unreasonable effectiveness of deep features as a perceptual metric,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:21:47.211673Z

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.

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