Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Differentially Private Next-Token Prediction of Large Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.15638.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T20:51:49.965171Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T08:30:31.802243Z
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 da358724-4a08-4e93-a6b3-b2832b627140 · 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 Differentially Private Next-Token Prediction of Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T20:51:49.965171Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c47d3da-719d-4a13-967b-ab2e080309d1 · 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 Next-Token Prediction of Large Language Models
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T06:52:07.911147Z
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 ab759da2-91cb-41d4-beb0-ec271609a92d · inbound
Balancing Utility and Privacy: Dynamically Private SGD with Random Projection cites this paper.
Balancing Utility and Privacy: Dynamically Private SGD with Random Projection Differentially Private Next-Token Prediction of Large Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:11:48.680282Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eaa295b3-25b8-467f-99b4-dab067f73d5d · inbound
Public Data Assisted Differentially Private In-Context Learning cites this paper.
Public Data Assisted Differentially Private In-Context Learning Differentially Private Next-Token Prediction of Large Language Models
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T17:28:48.574745Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9dd6a80-1c1c-4795-b858-c779c2f140ad · inbound
Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning cites this paper.
Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning Differentially Private Next-Token Prediction of Large Language Models
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T08:30:31.806336Z
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.