Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2403.09766.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:38:17.370563Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-09T12:56:14.842852Z
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 e43542ff-2dbe-4099-94ca-8c6b8de0e925 · 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 An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:38:17.370563Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b45362ca-7991-4124-bcab-7b76a3acb5e4 · 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 An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 95
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T19:45:19.312482Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 37e12be3-0ec8-48d6-967f-f8e319d40979 · 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 An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:40:54.618030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c99af47d-ff18-4cfe-93cf-7592dcb47e9c · inbound
On Surjectivity of Neural Networks: Can you elicit any behavior from your model? cites this paper.
On Surjectivity of Neural Networks: Can you elicit any behavior from your model? An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:00:48.734340Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d016811-84fe-4a79-ab44-e7ac00b487d1 · inbound
Jailbreaking Frontier Foundation Models Through Intention Deception cites this paper.
Jailbreaking Frontier Foundation Models Through Intention Deception An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:11:13.983178Z
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 2c1449a6-031b-4863-a898-cb8ebfe694a2 · 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 An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T17:23:36.813954Z
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 88153bfa-467f-4f3f-a148-4ec3afaa9904 · inbound
JECA^2: Judgment-Explanation Consistent Adversarial Attack against Forensic Vision-Language Models cites this paper.
JECA^2: Judgment-Explanation Consistent Adversarial Attack against Forensic Vision-Language Models An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 19
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T13:23:28.093125Z
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 7285edf7-345d-4d10-b77b-38357ef2d75c · inbound
Improving Adversarial Transferability on Vision-Language Pre-training Models via Surrogate-Specific Bias Correction cites this paper.
Improving Adversarial Transferability on Vision-Language Pre-training Models via Surrogate-Specific Bias Correction An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:37:37.258447Z
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 6460664e-a09a-4c5a-a2e2-c88e571c3d3e · inbound
On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces cites this paper.
On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models
Reference 44
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T12:56:14.845099Z
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.