Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Practical Defences Against Model Inversion Attacks for Split Neural Networks
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.05743.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:01:34.984721Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T16:06:31.902101Z
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 7cd24111-58f3-4ee0-98ec-5dfdeefdf199 · inbound
Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization cites this paper.
Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization Practical Defences Against Model Inversion Attacks for Split Neural Networks
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:01:34.984721Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98265150-675f-452d-8838-ab1d683dcf4c · inbound
Split and Aggregation Learning for Foundation Models Over Mobile Embodied AI Network (MEAN): A Comprehensive Survey cites this paper.
Split and Aggregation Learning for Foundation Models Over Mobile Embodied AI Network (MEAN): A Comprehensive Survey Practical Defences Against Model Inversion Attacks for Split Neural Networks
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:06:31.915791Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.