Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.05159.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:09:54.660030Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T15:01:35.934920Z
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 93169975-4eee-496d-9de0-b378bda7fa65 · inbound
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding cites this paper.
Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:09:54.660030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3decad8c-9552-4b14-8cc6-ec607775d66a · inbound
Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey cites this paper.
Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
Reference 107
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T21:58:41.182512Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9394d20a-9389-4544-9ef4-e42818fed8ec · 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 MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T15:01:35.945171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.