Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.16530.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:58:10.727240Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-11T01:47:46.606750Z
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 23fe4c91-e994-4a78-9b44-c764cf03bb17 · 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 Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 150
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:58:10.727240Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b45c227-2729-4afa-bb7b-3ecb9a806681 · inbound
Beyond Latency: A System-Level Characterization of MPC and FHE for PPML cites this paper.
Beyond Latency: A System-Level Characterization of MPC and FHE for PPML Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:46:12.347150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 58ccbb44-64ce-4490-a368-b36749ed7e12 · 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 Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T07:16:54.804656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 98b0408a-58a0-4cfe-9459-2a735bf7c751 · inbound
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs cites this paper.
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-07-08T20:45:37.005325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 693d60ab-ee68-494b-8621-97666eac456e · inbound
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs cites this paper.
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-07-11T01:47:46.626703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 892c6afc-ac0c-4a32-8631-e61bba66e696 · inbound
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs cites this paper.
LibFHE: A Numba-Based CUDA-Python Library for Non-RNS CKKS-BGV Fully Homomorphic Encryption on GPUs Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T16:09:54.356430Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.