Paper Citation Record · LEDGER

Dynamic Differential-Privacy Preserving SGD

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2111.00173.

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

pith.paper-citation-record.v1
2111.00173 v3

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:05:17.755433Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T19:11:46.544655Z

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 21de7318-90b5-49b2-b856-899f44b21ac4 · inbound

Steps Adaptive Decay DPSGD: Enhancing Performance on Imbalanced Datasets with Differential Privacy with HAM10000 cites this paper.

Steps Adaptive Decay DPSGD: Enhancing Performance on Imbalanced Datasets with Differential Privacy with HAM10000 Dynamic Differential-Privacy Preserving SGD

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T19:05:17.755433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7da81dbc-830e-4ff3-b96f-26b6ece1dd74 · inbound

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling cites this paper.

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling Dynamic Differential-Privacy Preserving SGD

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:11:46.547966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 60244d8b-4800-4f20-8196-b2b9ddeb5475 · inbound

Balancing Utility and Privacy: Dynamically Private SGD with Random Projection cites this paper.

Balancing Utility and Privacy: Dynamically Private SGD with Random Projection Dynamic Differential-Privacy Preserving SGD

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:11:48.309059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20bb1f79-2e83-48a0-95ae-c1b84c6bb24e · inbound

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models cites this paper.

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models Dynamic Differential-Privacy Preserving SGD

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:31:25.479227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.