Paper Citation Record · LEDGER

Output Perturbation for Differentially Private Convex Optimization: Faster and More General

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2102.04704.

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

pith.paper-citation-record.v1
2102.04704 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:39:20.249398Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:06:15.766100Z

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 1b1b3c31-a872-4cc4-a79d-fdde943c660e · inbound

Privacy Amplification Through Synthetic Data: Insights from Linear Regression cites this paper.

Privacy Amplification Through Synthetic Data: Insights from Linear Regression Output Perturbation for Differentially Private Convex Optimization: Faster and More General

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T10:39:20.249398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f123f411-0804-49f6-bed2-069e8fd75dd2 · inbound

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy cites this paper.

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy Output Perturbation for Differentially Private Convex Optimization: Faster and More General

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:58:13.029768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aa5d2986-1d44-41b8-85f3-7a612ea1c98b · inbound

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy cites this paper.

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy Output Perturbation for Differentially Private Convex Optimization: Faster and More General

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T00:53:53.603910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a3e2a034-a1f0-4b09-884a-df62b4de693a · inbound

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses cites this paper.

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses Output Perturbation for Differentially Private Convex Optimization: Faster and More General

Reference 187

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:06:15.767736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.