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Paper Citation Record · LEDGER

Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.03554.

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

pith.paper-citation-record.v1
2408.03554 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:38:17.535246Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:38:02.924633Z

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 b379bd8c-3a69-4d0d-b58a-fa792b22b576 · 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 Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

Reference 120

Resolution
unresolved
no resolver link, observed 2026-08-08T15:38:17.535246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:38:17.535246Z digest=sha256:946cbc28009190760ee5f238977de36482c642b29bb140b7231a8a396ec7fe08

Observation 66bdaf77-91db-4f8e-94f4-bc4d9b3abb2d · inbound

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

Invisible Injections: Exploiting Vision-Language Models Through Steganographic Prompt Embedding Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T11:54:43.102709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:54:43.102709Z digest=sha256:948c88cc11068d7b91d6e9a4aafe9e4aac9d2d952a81c3af4da6056d700291dc

Observation e9abbf7f-1f7f-47bf-9ac7-84ff298caac9 · inbound

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses cites this paper.

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-04T09:25:45.204025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:25:45.204025Z digest=sha256:550cccffd61a75be39bf3bf400be5c37039bbfa7ad19c99d18dde2629890b8c5

Observation 95283c95-ff55-4f52-ba7f-13caefec7b44 · 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 Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:38:02.926486Z

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=2026-05-13T17:34:10.089555Z digest=sha256:dc5733a0ae81cfe42fd2de3d510da12edd4c1edb798b66939078524719386a63

Observation fe9fd81b-398b-4ab8-bdf6-1cd6b8431311 · 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 Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T00:41:28.336206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:41:28.336206Z digest=sha256:dcc492abb678af63cdafb79108767dde3d3d842793ec47786f5411af5751a575