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Paper Citation Record · LEDGER

Verifiable evaluations of machine learning models using zkSNARKs

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.02675.

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

pith.paper-citation-record.v1
2402.02675 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:24:06.581455Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:57:32.613339Z

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 7117ce14-b77a-45cc-85cb-927f73be15b6 · inbound

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? cites this paper.

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? Verifiable evaluations of machine learning models using zkSNARKs

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-16T12:24:06.581455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:24:06.581455Z digest=sha256:31676eff44459d99628d2007b30aa5f4eec8b2b0b7682ba43995cf4b3f09a14c

Observation 7beb0e87-c7d3-4681-84dd-c72ffa70d061 · inbound

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks cites this paper.

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks Verifiable evaluations of machine learning models using zkSNARKs

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-16T06:06:57.514128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T06:06:57.514128Z digest=sha256:2e074b2241999a8c21cd948dc0394389154acf4c0256315499a183d32435e02c

Observation 4fadef4e-f29e-419e-9860-d263fec3f7bb · inbound

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

Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments Verifiable evaluations of machine learning models using zkSNARKs

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T21:45:03.990514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:03.990514Z digest=sha256:30f3af3c8b397f693a261b3781d3203899d7c89b9f8a9915c8ded2492fa9632c

Observation 4ef317c6-0d77-448d-895a-325d29630261 · inbound

Private, Verifiable, and Auditable AI Systems cites this paper.

Private, Verifiable, and Auditable AI Systems Verifiable evaluations of machine learning models using zkSNARKs

Reference 274

Resolution
unresolved
no resolver link, observed 2026-08-05T15:43:59.498751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:43:59.498751Z digest=sha256:ae4f8f60b373e46884adc62a421e5289f65142333d9be24be0290187e6f48269

Observation 03d477e1-acf5-44eb-8171-0f9d812f8fc8 · inbound

Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification cites this paper.

Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification Verifiable evaluations of machine learning models using zkSNARKs

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:30:52.199340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T19:46:23.836745Z digest=sha256:fd828374a622da1a7fb3e9bf093c39fe202628b726a8defaae813a32fdd48504

Observation 2f61b76b-1dd9-4c00-aed0-6ccb1687b21a · inbound

Zero knowledge verification for frontier AI training is possible cites this paper.

Zero knowledge verification for frontier AI training is possible Verifiable evaluations of machine learning models using zkSNARKs

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-02T08:26:47.806295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T06:06:59.462289Z digest=sha256:64360bdb3b75042bceb724327d3c1acdd8f46ee645282064608dd46ac8b99c15

Observation 83d0a000-3cbf-4c26-9c86-6e7225b07dc3 · inbound

Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting cites this paper.

Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting Verifiable evaluations of machine learning models using zkSNARKs

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-07-03T01:57:32.614700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T16:11:36.483820Z digest=sha256:d7a213a84c5ba0ccaa19771d3680ae66f8711188d746fb617f9a87b4061ac97b

Observation 9d3a6239-da5e-4ee1-b564-dd9ab937f56a · inbound

Privacy-Preserving AI Verification via Minimal Information Disclosure cites this paper.

Privacy-Preserving AI Verification via Minimal Information Disclosure Verifiable evaluations of machine learning models using zkSNARKs

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T15:09:07.307257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:09:07.307257Z digest=sha256:1b934aeec02c5ecaf66ae173b24ff59ec94a137bf5c1a14032088a5cb5358160

Observation 52060627-6a10-41fb-830e-8cbd19c26165 · inbound

NiyamAI - An Intent-Bound AI Agent with Cryptographically Verifiable Guardrails using Zero-Knowledge Proofs cites this paper.

NiyamAI - An Intent-Bound AI Agent with Cryptographically Verifiable Guardrails using Zero-Knowledge Proofs Verifiable evaluations of machine learning models using zkSNARKs

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T13:45:43.974198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T13:45:43.974198Z digest=sha256:593616500b6c353b98d19a29aa5371e6ebd4c56b6443c4d3dc3ce2a98c7df9ec

Observation e4f5c83d-0f1f-4f57-9301-014ec67d760e · inbound

Repeated-Game Security for Restaking-Based Verifiable Inference cites this paper.

Repeated-Game Security for Restaking-Based Verifiable Inference Verifiable evaluations of machine learning models using zkSNARKs

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-14T04:25:21.588537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:25:21.588537Z digest=sha256:154b9836ef532887ef98cad492f5a4286ed82b8972fbcd97256571298e2c98cb