Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.12636.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:51:32.003169Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T04:42:33.920665Z
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 6703e8b3-1726-4094-b904-2296288f5171 · inbound
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety cites this paper.
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Reference 224
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T04:42:33.923841Z
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 a6fead6f-3ab2-4daa-9c6e-e8d303eb6951 · inbound
Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models cites this paper.
Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:32.003169Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef17e8f2-5678-412c-bee2-392281cda67e · inbound
Attacking Attention of Foundation Models Disrupts Downstream Tasks cites this paper.
Attacking Attention of Foundation Models Disrupts Downstream Tasks Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:09:10.053287Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57a58b9d-7726-4144-9726-211544a118ce · inbound
TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models cites this paper.
TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T14:23:21.483785Z
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 156e28e3-1779-4883-9642-29205ad7bd1b · inbound
On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline cites this paper.
On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T00:37:19.179078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.