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Paper Citation Record · LEDGER

Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.03741.

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

pith.paper-citation-record.v1
2409.03741 v1

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:58:52.862425Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:18:33.179852Z

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 13adcfa1-90c6-4bea-bcbe-86ba57a53b24 · inbound

Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning cites this paper.

Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:52.862425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:52.862425Z digest=sha256:2055ab34e24f2dc1073f09f4a21b8af7c187e54b4f697c85b97d2ab5d6f01393

Observation 507a3e6d-19e8-42d6-8c85-69cbb9a05af4 · inbound

CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage cites this paper.

CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?

Reference 71

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:18:33.358522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T15:18:30.023155Z digest=sha256:2494f1896d443fb6e7381aa564bf1c79e02ee1ec306777446ec7880d02116481