Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.01584.
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 2026-08-06T15:58:03.790797Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T07:16:54.810938Z
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 007e58ed-e46f-4f43-969f-188c4b3f7f46 · 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 TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:58:03.790797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7bb1b7e7-1585-4fec-b809-c99472a75c40 · inbound
Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks cites this paper.
Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T07:16:54.812262Z
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.