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Paper Citation Record · LEDGER

Differentially Private Model Publishing for Deep Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.02200.

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

pith.paper-citation-record.v1
1904.02200 v5

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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:24:05.336113Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T11:06:04.765451Z

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 b2ba5940-6753-4532-8526-308d9904de16 · inbound

AdaCliP: Adaptive Clipping for Private SGD cites this paper.

AdaCliP: Adaptive Clipping for Private SGD Differentially Private Model Publishing for Deep Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-14T12:24:05.336113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:24:05.336113Z digest=sha256:eaf058cdbbfb8d40cee5fd5f7ffa9120c53ca8e93ee8062902d35ee8db5e26e5

Observation 238f758b-3e85-4fd0-a338-73d72341dab9 · inbound

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis cites this paper.

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis Differentially Private Model Publishing for Deep Learning

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:06:04.772465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T11:06:04.722850Z digest=sha256:052dacf836be6ed46a33f4bba5e525484b3c5b6f4f9d4118a34dbc8c27fc8a2a