Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.01749.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-20T13:35:02.869657Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T13:38:19.382911Z
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 e523873f-85eb-4f59-9ba4-976126e1b107 · inbound
InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy cites this paper.
InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T06:52:07.866988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 703c934b-2fd0-4bed-b3d3-9aa1ebcdd0c7 · inbound
SynBench: A Benchmark for Differentially Private Text Generation cites this paper.
SynBench: A Benchmark for Differentially Private Text Generation Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T16:46:37.526184Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 59c3cd35-42e4-45e6-b95c-c92d10c99da1 · inbound
DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models cites this paper.
DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:38:19.384758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.