Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Going Grayscale: The Road to Understanding and Improving Unlearnable Examples
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.13244.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-14T10:41:43.164852Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T20:42:57.368369Z
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 77caadef-6dda-413f-b26c-09b6fdeb1b83 · inbound
SoK: Unlearnability and Unlearning for Model Dememorization cites this paper.
SoK: Unlearnability and Unlearning for Model Dememorization Going Grayscale: The Road to Understanding and Improving Unlearnable Examples
Reference 128
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:47:04.248103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4fb2ebe8-69bd-4fa8-93f0-0fea79cb8137 · inbound
SoK: A Comprehensive Analysis of the Current Status of Neural Tangent Generalization Attacks with Research Directions cites this paper.
SoK: A Comprehensive Analysis of the Current Status of Neural Tangent Generalization Attacks with Research Directions Going Grayscale: The Road to Understanding and Improving Unlearnable Examples
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:42:57.371673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6a92c287-45cd-4018-87e2-6bfcff1f0bb2 · inbound
DiffUE: Enhancing Utility-Unlearnability Trade-off of Unlearnable Examples via Diffusion Autoencoders cites this paper.
DiffUE: Enhancing Utility-Unlearnability Trade-off of Unlearnable Examples via Diffusion Autoencoders Going Grayscale: The Road to Understanding and Improving Unlearnable Examples
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T10:41:43.164852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.