Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DeepReShape: Redesigning Neural Networks for Efficient Private Inference
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2304.10593.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:58:10.561735Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T15:44:00.141717Z
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 fed13c7f-638a-43db-8bc5-4eefcbd2b5f2 · inbound
Towards Efficient Privacy-Preserving Machine Learning: A Systematic Review from Protocol, Model, and System Perspectives cites this paper.
Towards Efficient Privacy-Preserving Machine Learning: A Systematic Review from Protocol, Model, and System Perspectives DeepReShape: Redesigning Neural Networks for Efficient Private Inference
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:58:10.561735Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f090a90c-e8e5-4442-8418-4b069458f64c · inbound
Private, Verifiable, and Auditable AI Systems cites this paper.
Private, Verifiable, and Auditable AI Systems DeepReShape: Redesigning Neural Networks for Efficient Private Inference
Reference 135
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T15:44:00.144927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 62828d6d-42d5-47f7-a431-b18b018a72c6 · inbound
CrypTorch: PyTorch-based Auto-tuning Compiler for Machine Learning with Multi-party Computation cites this paper.
CrypTorch: PyTorch-based Auto-tuning Compiler for Machine Learning with Multi-party Computation DeepReShape: Redesigning Neural Networks for Efficient Private Inference
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T20:28:53.412058Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.