Paper Citation Record · LEDGER

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.03724.

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

pith.paper-citation-record.v1
2312.03724 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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:50:04.655168Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T06:52:07.885299Z

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 b64c1624-f40a-4ca5-a4cd-b4d41feaf166 · inbound

RAG with Differential Privacy cites this paper.

RAG with Differential Privacy DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T00:50:04.655168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1c5c8ca-a98a-43f5-89ea-25bff54e137f · inbound

Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs cites this paper.

Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T20:51:49.979086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1c1a4b2-a234-4d46-a4c5-d8cceae247e9 · inbound

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs cites this paper.

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-06T23:51:20.136653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bba56f14-d0ad-41c5-b818-9f518b29ee89 · 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 DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:52:07.887816Z

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.