Paper Citation Record · LEDGER

Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2405.10529.

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

pith.paper-citation-record.v1
2405.10529 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:45:19.868976Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T06:17:42.481821Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 39c2234b-993c-4dc9-968a-602b60e1a764 · 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 Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 130

Resolution: unresolved; no resolver link, observed 2026-08-07T19:45:19.868976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2695b31c-6fb7-47be-871f-bf585facd308 · inbound

Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack cites this paper.

Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:22:02.650913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 892363c9-d243-47b9-904e-b23eb3085f1a · inbound

VSF-Med:A Vulnerability Scoring Framework for Medical Vision-Language Models cites this paper.

VSF-Med:A Vulnerability Scoring Framework for Medical Vision-Language Models Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:01:04.671789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff24a6f7-1b78-4c9c-961c-100377eb7315 · inbound

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

Invisible Injections: Exploiting Vision-Language Models Through Steganographic Prompt Embedding Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T11:54:43.097851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b733e4f-4090-402c-90a4-f64066d06207 · inbound

A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning cites this paper.

A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:38:02.909348Z

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 e3ca8679-fb0e-4de2-a6b0-3df3bc05be76 · inbound

SnapGuard: Lightweight Prompt Injection Detection for Screenshot-Based Web Agents cites this paper.

SnapGuard: Lightweight Prompt Injection Detection for Screenshot-Based Web Agents Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:06:17.742460Z

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 22083a23-42a6-4d7a-ad66-b8fb85b64c4c · inbound

A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation cites this paper.

A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-20T17:23:36.801915Z

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 8daca7ca-4232-4be0-8396-010f66b2c9cd · inbound

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges cites this paper.

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 101

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:27:31.082224Z

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 1e2f8ced-afc5-44d0-82b9-d651ab57bf92 · inbound

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models cites this paper.

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T06:17:42.483246Z

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 dce3be7f-8d56-444b-bdfd-0d8ff1669e31 · inbound

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models cites this paper.

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-15T10:53:29.444919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2778dff-66b4-47cf-9601-805d9831e2c5 · inbound

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models cites this paper.

Auditing Inference-Time Defense Evaluation for Multimodal Large Language Models Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T11:57:02.205247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 148ef1f2-5f47-4045-8f32-343e0f194c93 · inbound

Devil in the Lens: Analyzing and Defending Physical Prompt Injection Against Vision-Language Models on Wearable Devices cites this paper.

Devil in the Lens: Analyzing and Defending Physical Prompt Injection Against Vision-Language Models on Wearable Devices Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T13:02:42.673767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.