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Paper Citation Record · LEDGER

Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.09060.

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

pith.paper-citation-record.v1
2311.09060 v2

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:42:07.291500Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T11:42:08.813372Z

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 a4343104-c8a9-4418-9765-cea366588603 · inbound

Breaking Down Bias: On The Limits of Generalizable Pruning Strategies cites this paper.

Breaking Down Bias: On The Limits of Generalizable Pruning Strategies Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-08T11:42:08.818872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:42:07.291500Z digest=sha256:9394054cf1e29e88032760b1885b10d01ec748c59e566eac0d50ebae808b4782

Observation 91abb483-006a-4da0-a612-a0d24d1a58da · inbound

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation cites this paper.

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T00:46:09.936979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:46:09.936979Z digest=sha256:a7cfb1bae92a14d73d4110bce7e9533c9ef0019d2570ba9307359992f627d772