Paper Citation Record · LEDGER

Towards more transferable adversarial attack in black-box manner

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2505.18097.

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

pith.paper-citation-record.v1
2505.18097 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:41:11.853919Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

40 of 40 outbound references displayed

verified exact1
verified fuzzy20
unresolved19
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c7ee68e-ccd1-41c3-a309-c34651fc2586 · outbound

This paper cites Intriguing properties of neural networks.

Towards more transferable adversarial attack in black-box manner Intriguing properties of neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:16.713724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6cb7494b-8380-45cf-9d46-ca3e40420409 · outbound

This paper cites A grey-box attack against latent diffusion model-based image editing by posterior collapse.

Towards more transferable adversarial attack in black-box manner A grey-box attack against latent diffusion model-based image editing by posterior collapse

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:08.367380Z

Source-reported events for the cited work

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Observation 284c764e-1611-4958-bafe-dac8b9e5f6f1 · outbound

This paper cites A survey of recent backdoor attacks and defenses in large language models.

Towards more transferable adversarial attack in black-box manner A survey of recent backdoor attacks and defenses in large language models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:16.431346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f616c61b-6819-47ed-b17d-55e593daf5b1 · outbound

This paper cites A white-box false positive adversarial attack method on contrastive loss based offline handwritten signature verification models.

Towards more transferable adversarial attack in black-box manner A white-box false positive adversarial attack method on contrastive loss based offline handwritten signature verification models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:16.265780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d4b4651-6cd3-423a-8591-11d368dce6d9 · outbound

This paper cites Threats and defenses in the federated learning life cycle: A comprehensive survey and challenges.

Towards more transferable adversarial attack in black-box manner Threats and defenses in the federated learning life cycle: A comprehensive survey and challenges

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:16.108952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1c4318c-a6da-43d7-b404-45b452bc5b1b · outbound

This paper cites Breaking PEFT Limitations: Leveraging Weak-to-Strong Knowledge Transfer for Backdoor Attacks in LLMs.

Towards more transferable adversarial attack in black-box manner Breaking PEFT Limitations: Leveraging Weak-to-Strong Knowledge Transfer for Backdoor Attacks in LLMs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:08.810460Z

Source-reported events for the cited work

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Observation dfbb2cdf-6b65-4027-87c2-89b8ed687af3 · outbound

This paper cites Boosting adversarial attacks with momentum.

Towards more transferable adversarial attack in black-box manner Boosting adversarial attacks with momentum

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:15.917766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 86fe32d9-41ce-4346-92e4-20a6d88fc16b · outbound

This paper cites Artwork protection against neural style transfer using locally adaptive adversarial color attack.

Towards more transferable adversarial attack in black-box manner Artwork protection against neural style transfer using locally adaptive adversarial color attack

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:15.656860Z

Source-reported events for the cited work

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Observation 9532172d-b8eb-4688-b50d-52789c4ad60c · outbound

This paper cites Meta-attack: Class-agnostic and model-agnostic physical adversarial attack.

Towards more transferable adversarial attack in black-box manner Meta-attack: Class-agnostic and model-agnostic physical adversarial attack

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:15.367205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d6d5430f-82b0-45e6-a189-07088747e992 · outbound

This paper cites Diffusion-based adversarial sample generation for improved stealthiness and controllability.Advances in Neural Information Processing Systems, 36:2894–2921, 2023.

Towards more transferable adversarial attack in black-box manner Diffusion-based adversarial sample generation for improved stealthiness and controllability.Advances in Neural Information Processing Systems, 36:2894–2921, 2023

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:15.201497Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 07122a67-2afe-486b-8179-63a193dd9347 · outbound

This paper cites Diffusion models for adversarial purification.

Towards more transferable adversarial attack in black-box manner Diffusion models for adversarial purification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:14.908549Z

Source-reported events for the cited work

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Observation dfdcbbf5-822c-46bb-84b0-cd648b8bd92e · outbound

This paper cites Diffusion Models Beat GANs on Image Synthesis.

Towards more transferable adversarial attack in black-box manner Diffusion Models Beat GANs on Image Synthesis

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:09.453299Z

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Observation 8d1151aa-d6c1-4bf3-ba3c-8523809ea4c1 · outbound

This paper cites Explaining and harnessing adversar- ial examples.

Towards more transferable adversarial attack in black-box manner Explaining and harnessing adversar- ial examples

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:14.630892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22eacdc8-071e-40c4-a121-3a5269b5ca7c · outbound

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

Towards more transferable adversarial attack in black-box manner Towards deep learning models resistant to adversarial attacks

Reference 14

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Observation 39a9d347-34fa-4363-8258-2c5241c81a30 · outbound

This paper cites Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models.

Towards more transferable adversarial attack in black-box manner Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:09.746841Z

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Observation 76147a81-3587-43b2-9651-54f88f9e736b · outbound

This paper cites Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models.

Towards more transferable adversarial attack in black-box manner Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:14.320469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c50b569a-ea91-4f55-989e-55877f0b7d89 · outbound

This paper cites Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.

Towards more transferable adversarial attack in black-box manner Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:09.931290Z

Source-reported events for the cited work

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Observation 5c806b53-d032-4f3e-af75-afd98e02e1d4 · outbound

This paper cites Rethinking model ensemble in transfer-based adversarial attacks.

Towards more transferable adversarial attack in black-box manner Rethinking model ensemble in transfer-based adversarial attacks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:14.080657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 03ed648d-9a33-4979-bf45-a98f248d1230 · outbound

This paper cites Understanding Model Ensemble in Transferable Adversarial Attack.

Towards more transferable adversarial attack in black-box manner Understanding Model Ensemble in Transferable Adversarial Attack

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:41:12.066759Z

Source-reported events for the cited work

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Observation aa34e1a1-6ff2-42bb-8187-4fba9c942319 · outbound

This paper cites Diffusion models for imperceptible and transferable adversarial attack.

Towards more transferable adversarial attack in black-box manner Diffusion models for imperceptible and transferable adversarial attack

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:13.840393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d1a3219d-b8a5-40ec-ae11-342a45a733a7 · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.

Towards more transferable adversarial attack in black-box manner Deep unsuper- vised learning using nonequilibrium thermodynamics

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:10.304189Z

Source-reported events for the cited work

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Observation 2c9a3d45-82ea-44b8-8558-17760bd5a71f · outbound

This paper cites Denoising diffusion probabilistic models.

Towards more transferable adversarial attack in black-box manner Denoising diffusion probabilistic models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:10.402349Z

Source-reported events for the cited work

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Observation 8febf8f1-a4ee-4921-9015-67a4c9e43fa8 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Towards more transferable adversarial attack in black-box manner Classifier-Free Diffusion Guidance

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:10.518510Z

Source-reported events for the cited work

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Observation 92421e20-8c5b-4705-8869-a0eed95a713a · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

Towards more transferable adversarial attack in black-box manner High- resolution image synthesis with latent diffusion models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:13.569393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 24bbb228-de02-4514-9cd5-07bf22672352 · outbound

This paper cites Instant ad- versarial purification with adversarial consistency distillation.

Towards more transferable adversarial attack in black-box manner Instant ad- versarial purification with adversarial consistency distillation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:13.155109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 28ad529e-875c-46cc-8718-ca76793999c1 · outbound

This paper cites Denoising diffusion implicit models.

Towards more transferable adversarial attack in black-box manner Denoising diffusion implicit models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:10.781655Z

Source-reported events for the cited work

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Observation 2ec7e366-4bf4-44ca-981b-c0dd036eb3ee · outbound

This paper cites Variational diffusion models.

Towards more transferable adversarial attack in black-box manner Variational diffusion models

Reference 27

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Source-reported events for the cited work

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Observation f850ec1f-3c3b-4a96-8e9b-c760dba48546 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

Towards more transferable adversarial attack in black-box manner Score-based generative modeling through stochastic differential equations

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:10.931789Z

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Observation c793e992-9a05-4370-815c-c7d65c6e5cde · outbound

This paper cites Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks.

Towards more transferable adversarial attack in black-box manner Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:11.038741Z

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Observation dc5fd4f6-c1dc-4071-82e5-39419118a9f2 · outbound

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

Towards more transferable adversarial attack in black-box manner Imagenet: A large- scale hierarchical image database

Reference 30

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Observation f66a0df4-078a-4827-a885-36d1b6116a4b · outbound

This paper cites Deep residual learning for im- age recognition.

Towards more transferable adversarial attack in black-box manner Deep residual learning for im- age recognition

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:12.899428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e355ea0f-25e6-4a3b-9409-05d0ea6719e1 · outbound

This paper cites Wide residual networks.

Towards more transferable adversarial attack in black-box manner Wide residual networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:12.727119Z

Source-reported events for the cited work

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Observation b15c752a-1876-4a87-95db-be913cbc1462 · outbound

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

Towards more transferable adversarial attack in black-box manner Image quality assessment: from error visibility to structural similarity

Reference 33

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Observation 6cf3927f-f110-42e0-b4ef-01c8904d8729 · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

Towards more transferable adversarial attack in black-box manner Efros, Eli Shechtman, and Oliver Wang

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:12.579156Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e0a3936-b435-425e-9761-fc7319479811 · outbound

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

Towards more transferable adversarial attack in black-box manner Pytorch: An imperative style, high-performance deep learning library

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:11.495022Z

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Observation 7fe46835-5bfa-4855-b2c4-ec64bded2c43 · outbound

This paper cites Torch.manual_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision.

Towards more transferable adversarial attack in black-box manner Torch.manual_seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:11.564844Z

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Observation 5d270535-0b10-4a8d-8807-928bd20ae11f · outbound

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

Towards more transferable adversarial attack in black-box manner Very deep convolutional networks for large-scale image recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:12.460387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0c2c448f-c5e7-40c7-886a-351413a76cda · outbound

This paper cites Microsoft coco: Common objects in context.

Towards more transferable adversarial attack in black-box manner Microsoft coco: Common objects in context

Reference 38

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Observation f5da79d6-9ca5-4b34-b89b-d243c4f3392a · outbound

This paper cites Benchmarking Detection Transfer Learning with Vision Transformers.

Towards more transferable adversarial attack in black-box manner Benchmarking Detection Transfer Learning with Vision Transformers

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:11.779207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3494d486-52c8-4674-8000-76392a1560ac · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Towards more transferable adversarial attack in black-box manner Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:12.347418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

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