Paper Citation Record · LEDGER

Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.13055.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2407.13055 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:44:14.889043Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T22:46:12.368904Z

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 be1b389d-a31c-472c-9e1e-a948b7789001 · inbound

FIDESlib: A Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs cites this paper.

FIDESlib: A Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:14.889043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e2c82b7-98a1-4c05-9007-768ebc934fc8 · 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 Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-06T15:58:10.589863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbfd66f4-1b4d-47ef-b522-c00a4f398820 · 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 Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T20:28:51.710176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 471f94e5-09c1-4a81-bd9e-381f6d25c2ca · inbound

FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption cites this paper.

FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T03:03:55.938141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 861d7b25-1bfa-4ab7-befc-a05d97bfc480 · 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 Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:46:12.375501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4b494e75-38e6-4e1c-8dd7-f9d7f214ad14 · inbound

GPU Acceleration of Sparse Fully Homomorphic Encrypted DNNs cites this paper.

GPU Acceleration of Sparse Fully Homomorphic Encrypted DNNs Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:56:03.356063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.