Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2307.12499.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T22:22:29.798769Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 157225b6-2294-4ad8-b00c-9077059f9323 · inbound
NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model cites this paper.
NODE-AdvGAN: Improving the transferability and perceptual similarity of adversarial examples by dynamic-system-driven adversarial generative model AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models
Reference 17
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-11T22:22:29.798769Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcac7236-98a3-44e5-afcd-2c87308a4693 · inbound
Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation cites this paper.
Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:28:32.004356Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91e150dd-4da1-4313-9b0e-e0b292691ebd · inbound
Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models cites this paper.
Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models AdvDiff: Generating Unrestricted Adversarial Examples using Diffusion Models
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-06-26T04:38:59.225016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.