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Paper Citation Record · LEDGER

Enhancing Data Privacy in Large Language Models through Private Association Editing

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.18221.

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

pith.paper-citation-record.v1
2406.18221 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:32:31.329825Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:27:08.829762Z

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 bd1cdebf-b555-411b-8754-01fbbfc1c1a1 · inbound

Position: Editing Large Language Models Poses Serious Safety Risks cites this paper.

Position: Editing Large Language Models Poses Serious Safety Risks Enhancing Data Privacy in Large Language Models through Private Association Editing

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T10:32:31.329825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:32:31.329825Z digest=sha256:3f524951543de875df753d9171664ba2bcfeca00746c7bf66fc38335bffe2f6a

Observation a97bd68f-7a00-4baf-8b8e-5f15bab8878f · inbound

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models cites this paper.

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models Enhancing Data Privacy in Large Language Models through Private Association Editing

Reference 35

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T05:27:08.834151Z

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.

source=arxiv_source observed=2026-08-07T05:27:08.693777Z digest=sha256:ed2cdc18b4dedb32458e9303f7cf318b2234e958535ecab08e8a69fb7438d060