Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1912.02631.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:26:12.287416Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T13:47:57.294612Z
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 01882546-abbb-4a65-86ed-e800b42e45f6 · inbound
Comet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity cites this paper.
Comet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:26:12.287416Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a1aebff-94f4-47cb-a224-d2a77e2ed755 · 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 Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:58:05.159420Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 634feedb-ccce-4627-937d-5e5fd0e608db · inbound
High-Throughput and Scalable Secure Inference Protocols for Deep Learning with Packed Secret Sharing cites this paper.
High-Throughput and Scalable Secure Inference Protocols for Deep Learning with Packed Secret Sharing Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T13:47:57.296913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.