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Paper Citation Record · LEDGER

Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.08970.

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

pith.paper-citation-record.v1
2501.08970 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:07:01.340318Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:45:05.939479Z

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 56d9f84d-fe71-4231-9a6e-e5c6a3d3602b · inbound

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance cites this paper.

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T15:07:01.340318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:07:01.340318Z digest=sha256:39ca9f2eeeccfe7eb08c8a2d12ec92f90a38d437e3c84d0a65285ab9e30926d3

Observation 22b32ded-9f40-45c6-b64d-9f3fc4545002 · inbound

Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments cites this paper.

Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:45:06.056924Z

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.

source=arxiv_source observed=2026-08-06T21:45:03.879794Z digest=sha256:28c1fa271676488d8d835b981e129b56401e65d0a17f52146f4bcf5cd19b720b