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Paper Citation Record · LEDGER

Fingerprinting Codes and the Price of Approximate Differential Privacy

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1311.3158.

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

pith.paper-citation-record.v1
1311.3158 v3

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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:19:34.308402Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:09:05.542533Z

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 adbb2fd1-66ac-4b9a-9427-78f47d5326fd · inbound

Privacy in Metalearning and Multitask Learning: Modeling and Separations cites this paper.

Privacy in Metalearning and Multitask Learning: Modeling and Separations Fingerprinting Codes and the Price of Approximate Differential Privacy

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T14:19:34.308402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:34.308402Z digest=sha256:bfb49a14fb58ba515b49ebe29c6144947aeb73cabf447d3c69576efcdb9578d4

Observation 0cc89389-ecc8-485b-b14a-c77107e393b7 · inbound

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning cites this paper.

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning Fingerprinting Codes and the Price of Approximate Differential Privacy

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T04:09:05.623766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:09:03.060030Z digest=sha256:efbf02f20a7b5d713b43435aeae1d0cf300a7cda2e1a42f30299dca16b1b389a