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Paper Citation Record · LEDGER

PrivacyMind: Large Language Models Can Be Contextual Privacy Protection Learners

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.02469.

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

pith.paper-citation-record.v1
2310.02469 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:02:34.445149Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T23:19:27.293596Z

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 50694f54-d48a-4496-8418-547d8dc01809 · inbound

Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions cites this paper.

Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions PrivacyMind: Large Language Models Can Be Contextual Privacy Protection Learners

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T20:02:34.445149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:02:34.445149Z digest=sha256:79a406fbca2bcb3e972969cfe9adafc3c0eae63f3e7a2fe31fb02533484a8205

Observation 7d6d5edd-2965-467a-86c4-84be5660a38b · inbound

PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction cites this paper.

PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction PrivacyMind: Large Language Models Can Be Contextual Privacy Protection Learners

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:19:27.298538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T23:19:26.932948Z digest=sha256:b21ebe8214da19942edd73ad915e6ad5962438b52426b7bb0eda36887efb32ea