Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FairProof : Confidential and Certifiable Fairness for Neural Networks
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.12572.
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 2026-08-15T22:12:07.646448Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T22:07:58.872059Z
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 8fdb6243-5f00-44e3-ae3e-9648379b2b23 · inbound
FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge cites this paper.
FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge FairProof : Confidential and Certifiable Fairness for Neural Networks
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:12:07.646448Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f95ac6b7-dbdc-4103-add0-465aa31f2959 · inbound
Justified Evidence Collection for Argument-based AI Fairness Assurance cites this paper.
Justified Evidence Collection for Argument-based AI Fairness Assurance FairProof : Confidential and Certifiable Fairness for Neural Networks
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T22:07:58.876424Z
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.
Observation 3d6d7ff3-4df3-421b-b2c4-7f9f6eaf5cf4 · inbound
Certified in Theory, Broken in Practice: Assumption Gaps in Cryptographic Model Certification cites this paper.
Certified in Theory, Broken in Practice: Assumption Gaps in Cryptographic Model Certification FairProof : Confidential and Certifiable Fairness for Neural Networks
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T06:40:23.390306Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.