Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Do Adversarially Robust ImageNet Models Transfer Better?
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2007.08489.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:35:09.153916Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T16:56:15.512747Z
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 221fd680-a00d-44c8-832c-604c11fbe910 · inbound
Killing it with Zero-Shot: Adversarially Robust Novelty Detection cites this paper.
Killing it with Zero-Shot: Adversarially Robust Novelty Detection Do Adversarially Robust ImageNet Models Transfer Better?
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:30:29.450912Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f5993c4-0347-4a62-b18d-64f31058304f · inbound
Energy-Aware Deep Learning on Resource-Constrained Hardware cites this paper.
Energy-Aware Deep Learning on Resource-Constrained Hardware Do Adversarially Robust ImageNet Models Transfer Better?
Reference 123
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:35:09.153916Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ca28d03-b333-491b-b406-e34987a0453f · inbound
Adversarial Examples Are Not Bugs, They Are Superposition cites this paper.
Adversarial Examples Are Not Bugs, They Are Superposition Do Adversarially Robust ImageNet Models Transfer Better?
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T16:56:15.614207Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.