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Paper Citation Record · LEDGER

Characterizing Structural Regularities of Labeled Data in Overparameterized Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2002.03206.

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

pith.paper-citation-record.v1
2002.03206 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:26:06.965592Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:25:23.249468Z

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 7a0f1248-5e44-452f-bba6-d7d24da67a4b · inbound

Laplace Sample Information: Data Informativeness Through a Bayesian Lens cites this paper.

Laplace Sample Information: Data Informativeness Through a Bayesian Lens Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:26:06.965592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:26:06.965592Z digest=sha256:feee09b69034716afbc63cfa8eda32db57a782ecf4bfc40968cb1744b61420bb

Observation db83ac53-054a-45b3-92fb-ea8df8817392 · inbound

Leveraging Per-Instance Privacy for Machine Unlearning cites this paper.

Leveraging Per-Instance Privacy for Machine Unlearning Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T14:29:49.200586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:49.200586Z digest=sha256:90eeb6297299a203e450a3a7b1358097daccca788423063a339ca8dc67de5be5

Observation 38efee1e-da5b-4f33-ae1e-08bd295cf146 · inbound

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning cites this paper.

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-05T22:09:05.177719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:09:05.177719Z digest=sha256:c77c7e9832ddcd304b9585bcdfd91fa21cee12d3ad48bee66a6a66eef1932e57

Observation 15f0aa66-b8b3-4bcf-8b1a-7c1f872fd96d · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:30:59.037423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T18:06:08.962042Z digest=sha256:554eac952f01c6ea38e9fc59d82d463e61491fa76707e90a294d1383e636790f

Observation 0089b6c8-9fea-4e79-aeab-f0cc545abc88 · inbound

Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling cites this paper.

Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:25:23.251750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-25T05:24:53.628214Z digest=sha256:fdd653c698b45a19f373165e4f7cff1248da7f28a85854b703015ef51b7b6373