Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.02744.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:06:26.125944Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T07:16:44.496659Z
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 2f9871e2-8ac7-4892-8083-bb8a262beaeb · inbound
AdaDPIGU: Differentially Private SGD with Adaptive Clipping and Importance-Based Gradient Updates for Deep Neural Networks cites this paper.
AdaDPIGU: Differentially Private SGD with Adaptive Clipping and Importance-Based Gradient Updates for Deep Neural Networks DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:06:26.125944Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5428bc2a-d55b-4042-960d-93c12fa43795 · inbound
When FinTech Meets Privacy: Securing Financial LLMs with Differential Private Fine-Tuning cites this paper.
When FinTech Meets Privacy: Securing Financial LLMs with Differential Private Fine-Tuning DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:55:04.898430Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b581f3a2-a4fa-417d-bbaa-984112d466e4 · inbound
When Do Fewer Coordinates Suffice in DP-SGD? cites this paper.
When Do Fewer Coordinates Suffice in DP-SGD? DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T07:16:44.498852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.