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Paper Citation Record · LEDGER

A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2407.07403.

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

pith.paper-citation-record.v1
2407.07403 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 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 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:38:17.114309Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:24:39.804121Z

Reference resolution

0 of 0 outbound references displayed

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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 8dd62ce0-0f80-4fd5-8f9e-40e6611c3926 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 95

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verified exact
arxiv_id, observed 2026-05-23T20:58:26.029473Z

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.

source=pdf_text observed=2026-05-23T20:58:16.237327Z digest=sha256:76ddcd2883f1000fa666a6b65f5addfeaf46cd8f60e897ec5bebd238ae801eb0

Observation c882a38d-0f9d-485d-b53a-65516bb50c15 · inbound

Hard-Label Black-Box Attacks on 3D Point Clouds cites this paper.

Hard-Label Black-Box Attacks on 3D Point Clouds A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 3

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verified exact
arxiv_id, observed 2026-05-23T08:37:44.862049Z

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.

source=pdf_text observed=2026-05-23T08:37:08.467026Z digest=sha256:2ca7ba4a95ab6de2a0e27b42b6cf1227412d6846d07824bbca8569d8513f4b34

Observation 0917c57e-d361-42ac-b959-9fe6f0a3b87c · inbound

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs cites this paper.

When Data Manipulation Meets Attack Goals: An In-depth Survey of Attacks for VLMs A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 20

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no resolver link, observed 2026-08-08T15:38:17.114309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:38:17.114309Z digest=sha256:1789531bb159164ab577b85974f3b91cac15e01ab31bda5901c754a62ab9b628

Observation 3d0cc952-6f93-4823-88dc-4dcd52f37639 · inbound

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 37

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no resolver link, observed 2026-08-07T19:45:18.489931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:45:18.489931Z digest=sha256:37187b59842de0e155b8c882c82cbfb82217c644153779d9dd49ac3d5c8c9570

Observation 32b9ac69-e3d6-4b00-839f-61bdc561c601 · 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 A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-23T00:15:14.853288Z

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.

source=pdf_text observed=2026-05-23T00:13:08.603115Z digest=sha256:58e8b3426fe896c63263167b917fa1b6677d29c9d9ea23a896f468ffd116a266

Observation 76a19b3e-210a-4668-8a87-d24970af5263 · inbound

Hierarchical Safety Realignment: Lightweight Restoration of Safety in Pruned Large Vision-Language Models cites this paper.

Hierarchical Safety Realignment: Lightweight Restoration of Safety in Pruned Large Vision-Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 17

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unresolved
no resolver link, observed 2026-08-07T15:11:04.716866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:11:04.716866Z digest=sha256:51f271e30c2165033bf2809dbc3f678924b8c2f0cb91a19b8a13ee1f5a1f3b95

Observation dc243864-cd91-4efc-9c81-290fc99b70c8 · inbound

BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization cites this paper.

BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 25

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no resolver link, observed 2026-08-07T15:03:59.647228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:03:59.647228Z digest=sha256:f7ca7a4750600bd80b45f5050c96006052a819503bf48b6ce86248e30ef3ff7b

Observation cedc2a29-f36b-4b2d-a00c-e406fd72200d · inbound

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection cites this paper.

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 21

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no resolver link, observed 2026-08-07T14:46:03.798834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:03.798834Z digest=sha256:2ed20b572b5d407052c1066d5355b3b0190f7dd42669786f00c91a4bf408e1e7

Observation 7fb282ec-aef9-4cc8-9396-e252390f3be7 · inbound

Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs cites this paper.

Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 28

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no resolver link, observed 2026-08-07T11:56:14.948476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:14.948476Z digest=sha256:5f8f6b848277f39b171b511f70a02d71f50059bd3ce2b15bf420d2f80e017593

Observation 311183e1-ba57-494f-b7ca-4fa9cfbb9f6b · inbound

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

Diffusion-based Cumulative Adversarial Purification for Vision Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 32

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no resolver link, observed 2026-08-07T10:59:18.054582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:59:18.054582Z digest=sha256:aa6ddc58545c4503c11f081f328af1378c7d9eb7b0533c1e1bb01e0e88ddee3f

Observation ed8edf02-b147-4fc6-ac77-8a5a5de05570 · inbound

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models cites this paper.

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 18

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unresolved
no resolver link, observed 2026-08-06T18:40:54.067388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:40:54.067388Z digest=sha256:6bc9c1e381757b0c0132e36c6fbd31d2ee41d5975dd602a95d0f07615bffd216

Observation 63d6651f-e8da-4f2f-b415-e3cce06f15ba · inbound

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding cites this paper.

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 46

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no resolver link, observed 2026-08-06T18:03:01.862985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:03:01.862985Z digest=sha256:5383dfe696c09eb88b3d23f0dbcc3e61d5aa5ab298dd437220bd76eb0b520924

Observation 7142993e-7a9f-488d-bfc9-66bc3f31608c · inbound

Anyone Can Jailbreak: Prompt-Based Attacks on LLMs and T2Is cites this paper.

Anyone Can Jailbreak: Prompt-Based Attacks on LLMs and T2Is A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 5

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no resolver link, observed 2026-08-06T12:23:03.941242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:23:03.941242Z digest=sha256:f2fc73c4d533fae9d8f454430ff5bcf073484cd0d66e5f6df1c0fbcee23a6b6b

Observation be887a7a-fa2c-4f19-b28d-02fa7b34b7ba · inbound

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security cites this paper.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.727842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.727842Z digest=sha256:aec803ba28905878a2c034e3b88af1280438150dd4e5c1d3d7fecfc7c30bcd27

Observation 88073051-5f25-467e-b525-4dcb62ae96af · inbound

Invisible Injections: Exploiting Vision-Language Models Through Steganographic Prompt Embedding cites this paper.

Invisible Injections: Exploiting Vision-Language Models Through Steganographic Prompt Embedding A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 1

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no resolver link, observed 2026-08-06T11:54:42.946018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:54:42.946018Z digest=sha256:10d5a57ccbc807647258161c3661b83cf9f8a8e801021d3fb534ecd29212461c

Observation cd77eacb-4564-4c74-b403-f36417a61e67 · inbound

The First Differentiable Transfer-Based Algorithm for Discrete MicroLED Repair cites this paper.

The First Differentiable Transfer-Based Algorithm for Discrete MicroLED Repair A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 15

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no resolver link, observed 2026-08-05T22:21:02.801582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:21:02.801582Z digest=sha256:270862e2e914209c11b6f0a0571051a93d44381b52820c3e9a17a71cc0ba2dd4

Observation 6ada323d-15db-4664-b52f-06f645d8c4c9 · inbound

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation cites this paper.

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 143

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no resolver link, observed 2026-08-05T20:31:45.892114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:31:45.892114Z digest=sha256:5e5758951e233169123ca9d59d2897f614cc84c8ffb3939be8076dd924409772

Observation 3e27a6b0-49c7-4296-a9fd-67485edf0f45 · inbound

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models cites this paper.

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 8

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verified exact
arxiv_id, observed 2026-05-18T15:26:33.861908Z

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.

source=pdf_text observed=2026-05-18T15:23:13.318310Z digest=sha256:226ba0421db32e80ca589d9cc6fa850b1dfc03386605d97125334785544daf8a

Observation e22cb968-630e-44fe-9025-d5ae556e722c · inbound

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models cites this paper.

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 8

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verified exact
arxiv_id, observed 2026-05-21T21:30:39.447565Z

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.

source=pdf_text observed=2026-05-21T21:28:59.898029Z digest=sha256:b0976d1ea968a156ab40573db25973f526c2de9bd727faedaf5ab9a28245c088

Observation 2846145d-382b-4083-8fa0-224cc3195575 · inbound

TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models cites this paper.

TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 2023

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no resolver link, observed 2026-08-04T13:52:15.314824Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:52:15.314824Z digest=sha256:40c4553598f3f4aa065ec8d385f66b908fb958e0c3392c163739cb960bf6ef17

Observation a29357e8-e064-431b-86bd-8b2f39bb2024 · inbound

FENCE: A Financial and Multimodal Jailbreak Detection Dataset cites this paper.

FENCE: A Financial and Multimodal Jailbreak Detection Dataset A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 13

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no resolver link, observed 2026-08-02T22:03:49.351667Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:03:49.351667Z digest=sha256:a128e8a9f7b559c12dbd96e1238e291f6c30db8b9cc32169a7155a455e3e4211

Observation a16e3c19-3995-4325-a328-36701531f6ed · inbound

When does learning pay off? A study on DRL-based dynamic algorithm configuration for carbon-aware scheduling cites this paper.

When does learning pay off? A study on DRL-based dynamic algorithm configuration for carbon-aware scheduling A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 12

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no resolver link, observed 2026-07-13T14:09:20.967908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T14:09:20.967908Z digest=sha256:d14e6d5accecec3e8abf8bfc42af5f46d6e4c64d9316c2dec989d4f1396e5253

Observation f83ad23b-de4e-498a-be5c-1cef73021209 · inbound

Efficient3D: A Unified Framework for Adaptive and Debiased Token Reduction in 3D MLLMs cites this paper.

Efficient3D: A Unified Framework for Adaptive and Debiased Token Reduction in 3D MLLMs A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 47

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verified exact
arxiv_id, observed 2026-05-13T19:48:11.418356Z

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.

source=pdf_text observed=2026-05-13T19:45:33.950587Z digest=sha256:9d442006317e783bd32fb8c9591773a6de430ab0e0777b74a8750b43558e2e71

Observation c294da9f-1e67-4451-92f9-69a9a63ba734 · inbound

To See is Not to Learn: Protecting Multimodal Data from Unauthorized Fine-Tuning of Large Vision-Language Model cites this paper.

To See is Not to Learn: Protecting Multimodal Data from Unauthorized Fine-Tuning of Large Vision-Language Model A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 37

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metadata mismatch
arxiv_id, observed 2026-05-15T02:39:40.903845Z

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.

source=arxiv_source observed=2026-05-15T02:38:37.358485Z digest=sha256:63c031cdfbd709478b7beb56be7a053420f17766da46a124878c07d72c7d4656

Observation e6c5f2d4-11c2-495d-9b25-64befe1c7f95 · inbound

Localization then Neutralization: Gradient-guided Token Suppression against Visual Prompt Injection Attack cites this paper.

Localization then Neutralization: Gradient-guided Token Suppression against Visual Prompt Injection Attack A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 4

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verified exact
arxiv_id, observed 2026-06-30T12:24:39.805804Z

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.

source=pdf_text observed=2026-06-30T12:19:12.910048Z digest=sha256:283bc4a2fbac29124521c64800e4ae13bde88dc07c07389fa4514190687ff603