Paper Citation Record · LEDGER

Diffusion Models for Adversarial Purification

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2205.07460.

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

pith.paper-citation-record.v1
2205.07460 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:40:55.064751Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:27:25.965269Z

Reference resolution

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e5993b06-7c4c-45af-9c06-d99c5b848108 · inbound

Graph Defense Diffusion Model cites this paper.

Graph Defense Diffusion Model Diffusion Models for Adversarial Purification

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:52:34.224746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ce9161d4-f897-4e0c-ab53-98338762bc93 · inbound

Boosting Adversarial Robustness and Generalization with Structural Prior cites this paper.

Boosting Adversarial Robustness and Generalization with Structural Prior Diffusion Models for Adversarial Purification

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-09T17:40:55.064751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4d3c428-8df6-4787-a645-f2c5f417750e · inbound

Improving Adversarial Robustness via Phase and Amplitude-aware Prompting cites this paper.

Improving Adversarial Robustness via Phase and Amplitude-aware Prompting Diffusion Models for Adversarial Purification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T00:55:56.256910Z

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Observation 3b0a971d-21fb-446c-be7c-b5ccdb3a9b26 · inbound

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion cites this paper.

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion Diffusion Models for Adversarial Purification

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T00:15:14.886294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f816d41b-8613-423a-a657-24322fa6a08f · inbound

TRAIL: Transferable Robust Adversarial Images via Latent diffusion cites this paper.

TRAIL: Transferable Robust Adversarial Images via Latent diffusion Diffusion Models for Adversarial Purification

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:58.305777Z

Source-reported events for the cited work

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Observation dbc64a64-c0f2-493f-be44-3ad245c44d6f · inbound

SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches via Super-Resolution GAN Models cites this paper.

SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches via Super-Resolution GAN Models Diffusion Models for Adversarial Purification

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:56.509341Z

Source-reported events for the cited work

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Observation 59559d1c-6f9f-4628-998e-f1a5393731c3 · inbound

Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking cites this paper.

Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking Diffusion Models for Adversarial Purification

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:12:08.650495Z

Source-reported events for the cited work

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Observation 9ee559b8-3d80-4510-b798-bb89eb1da984 · inbound

Silence is Golden: Leveraging Adversarial Examples to Nullify Audio Control in LDM-based Talking-Head Generation cites this paper.

Silence is Golden: Leveraging Adversarial Examples to Nullify Audio Control in LDM-based Talking-Head Generation Diffusion Models for Adversarial Purification

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:44:16.664363Z

Source-reported events for the cited work

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Observation 3984e668-6a61-4cf5-b8ac-d5d2636b1064 · inbound

Diffusion-based Cumulative Adversarial Purification for Vision Language Models cites this paper.

Diffusion-based Cumulative Adversarial Purification for Vision Language Models Diffusion Models for Adversarial Purification

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T10:59:19.095716Z

Source-reported events for the cited work

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Observation 31831e22-33dd-4576-aa7e-05c41a487748 · inbound

Diffusion models under low-noise regime cites this paper.

Diffusion models under low-noise regime Diffusion Models for Adversarial Purification

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:28:50.789545Z

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Observation 6d940d20-b81a-42e8-97de-901cd1f70086 · inbound

Encapsulated Composition of Text-to-Image and Text-to-Video Models for High-Quality Video Synthesis cites this paper.

Encapsulated Composition of Text-to-Image and Text-to-Video Models for High-Quality Video Synthesis Diffusion Models for Adversarial Purification

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:05.886229Z

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Observation 6a589f5b-b5a9-4d48-9015-06542f1e4e4b · inbound

First-Place Solution to NeurIPS 2024 Invisible Watermark Removal Challenge cites this paper.

First-Place Solution to NeurIPS 2024 Invisible Watermark Removal Challenge Diffusion Models for Adversarial Purification

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T14:40:54.510736Z

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Observation 85a3d6ef-1f22-417f-9aa3-9412a6c12bfd · inbound

A unifying Bayesian framework for adversarial robustness cites this paper.

A unifying Bayesian framework for adversarial robustness Diffusion Models for Adversarial Purification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T10:42:00.374901Z

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Observation 6bfb2f58-da90-4733-8934-6a6707af65b5 · inbound

NAPPure: Adversarial Purification for Robust Image Classification under Non-Additive Perturbations cites this paper.

NAPPure: Adversarial Purification for Robust Image Classification under Non-Additive Perturbations Diffusion Models for Adversarial Purification

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T09:44:17.356075Z

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Observation fd64c5ed-a2fa-453e-85c7-14b2f3b3408f · inbound

TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning cites this paper.

TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning Diffusion Models for Adversarial Purification

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:35:28.647735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2c001f9a-07cc-4d13-a13e-4155448f6715 · inbound

Enhancing Adversarial Robustness with Signed Distance Fields for Harmonizing Geometric Invariance and Texture cites this paper.

Enhancing Adversarial Robustness with Signed Distance Fields for Harmonizing Geometric Invariance and Texture Diffusion Models for Adversarial Purification

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T04:23:54.479153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af87611d-17cf-468f-8c2c-cf83d2f47146 · inbound

Towards Robust Content Watermarking Against Removal and Forgery Attacks cites this paper.

Towards Robust Content Watermarking Against Removal and Forgery Attacks Diffusion Models for Adversarial Purification

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:26:01.004856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f840480f-20fc-44fe-b05f-f549848ee6f8 · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems Diffusion Models for Adversarial Purification

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:06:02.810154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9085e489-4ba0-49db-9488-7b9d36d52821 · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems Diffusion Models for Adversarial Purification

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:20:58.082754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1eb393a-f47d-453e-86ea-d5486878cd97 · inbound

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems cites this paper.

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems Diffusion Models for Adversarial Purification

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:15:11.958728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 63804e53-6d6d-4731-a8a6-1cbdba489607 · inbound

Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations cites this paper.

Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations Diffusion Models for Adversarial Purification

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:01:18.466349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c1265dc-91e2-452f-b676-c236f587ead3 · inbound

PGID: Progressive Guided Inversion and Denoising for Robust Watermark Detection cites this paper.

PGID: Progressive Guided Inversion and Denoising for Robust Watermark Detection Diffusion Models for Adversarial Purification

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:31:28.260562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b368d867-ff40-4a3e-9b4b-5fa27809b8a3 · inbound

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps cites this paper.

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps Diffusion Models for Adversarial Purification

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:32:39.441301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5337a6a6-99c1-49b0-98cb-60bdea2c4135 · inbound

Compositional Adversarial Training for Robust Visual Watermarking cites this paper.

Compositional Adversarial Training for Robust Visual Watermarking Diffusion Models for Adversarial Purification

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-19T21:57:48.563773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 62b20559-e6de-4fc6-8943-83353099da30 · inbound

Investigating Adversarial Robustness of Multi-modal Large Language Models cites this paper.

Investigating Adversarial Robustness of Multi-modal Large Language Models Diffusion Models for Adversarial Purification

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:06:27.625796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8e0c1325-3b5e-43ad-bc75-b981fbd7338c · inbound

Beyond False Stability: High-Noise Drift Gating for Test-Time Adversarial Defenses in Vision-Language Models cites this paper.

Beyond False Stability: High-Noise Drift Gating for Test-Time Adversarial Defenses in Vision-Language Models Diffusion Models for Adversarial Purification

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:26.817544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 53738550-1b26-49fd-8da0-debf960e2fb3 · inbound

Stain-Aware Wavelet Regularization for Instant Adversarial Purification in Histopathology cites this paper.

Stain-Aware Wavelet Regularization for Instant Adversarial Purification in Histopathology Diffusion Models for Adversarial Purification

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:27:25.966902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 70c486cd-ef35-4a6a-b01e-c2b9a4831f71 · inbound

Adversarially Guided Diffusion for LiDAR Range Image Synthesis cites this paper.

Adversarially Guided Diffusion for LiDAR Range Image Synthesis Diffusion Models for Adversarial Purification

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T15:45:08.348933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b12f1e3e-a643-4e9a-a49d-b140b7c4775f · inbound

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models cites this paper.

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models Diffusion Models for Adversarial Purification

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T16:57:27.557413Z

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Observation 59773805-4db5-49ce-b21f-c37e2440c9d5 · inbound

VLAGuard: A Framework for Evaluating and Mitigating Physical Attention Hijacking in Vision-Language-Action Robots within Wireless Sensor Networks cites this paper.

VLAGuard: A Framework for Evaluating and Mitigating Physical Attention Hijacking in Vision-Language-Action Robots within Wireless Sensor Networks Diffusion Models for Adversarial Purification

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T00:41:28.937593Z

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Unavailable: canonical work link unavailable.

Observation 6c8ae63e-61ba-4009-9244-e7d4e2947e81 · inbound

Structure-Aware Robust Fine-Tuning: Defending Vision-Language-Action Robots Against Physical Attention Hijacking cites this paper.

Structure-Aware Robust Fine-Tuning: Defending Vision-Language-Action Robots Against Physical Attention Hijacking Diffusion Models for Adversarial Purification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T23:06:14.738049Z

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Unavailable: canonical work link unavailable.

Observation f1f0362c-90a0-4182-b3b6-ef05524ec83c · inbound

Any-OPD: Heterogeneous On-Policy Distillation for Flow-Matching Models via Representation-Space Bridging cites this paper.

Any-OPD: Heterogeneous On-Policy Distillation for Flow-Matching Models via Representation-Space Bridging Diffusion Models for Adversarial Purification

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T21:17:17.271571Z

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Unavailable: canonical work link unavailable.