Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.04507.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:04:29.625853Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T22:40:48.282692Z
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 0fa6f811-b05d-4edc-bc88-d3cdb4d87d0d · inbound
Do we really have to filter out random noise in pre-training data for language models? cites this paper.
Do we really have to filter out random noise in pre-training data for language models? FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:04:29.625853Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b923d382-f9d7-4a08-bc76-9a1c16e6fedf · inbound
zkSTAR: A zero knowledge system for time series attack detection enforcing regulatory compliance in critical infrastructure networks cites this paper.
zkSTAR: A zero knowledge system for time series attack detection enforcing regulatory compliance in critical infrastructure networks FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:07:41.714193Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 09eb0335-f648-413b-b98b-a9314f98ed71 · inbound
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates cites this paper.
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:40:48.331355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0fce2492-dd08-4a41-873f-18e301c21de9 · inbound
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates cites this paper.
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T09:41:56.414542Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.