Paper Citation Record · LEDGER

Certifiable Machine Unlearning for Linear Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2106.15093.

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

pith.paper-citation-record.v1
2106.15093 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:17.728024Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation daf5a2fb-8a92-4640-8902-fd0b404e5a59 · inbound

Machine Unlearning: A Comprehensive Survey cites this paper.

Machine Unlearning: A Comprehensive Survey Certifiable Machine Unlearning for Linear Models

Reference 111

Resolution: verified exact; arxiv_id, observed 2026-05-24T01:13:42.707203Z

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.

Observation 33046c43-92e4-4b75-8eb4-4e65df2e7ef4 · inbound

Towards Certified Unlearning for Deep Neural Networks cites this paper.

Towards Certified Unlearning for Deep Neural Networks Certifiable Machine Unlearning for Linear Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:03:30.808702Z

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.

Observation c28edc61-be2e-4b39-956b-8f0a45cb14b2 · inbound

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster cites this paper.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Certifiable Machine Unlearning for Linear Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.728024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03c3957c-8a53-4d58-acfc-dba1b84dde35 · inbound

How to Protect Models against Adversarial Unlearning? cites this paper.

How to Protect Models against Adversarial Unlearning? Certifiable Machine Unlearning for Linear Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T17:26:33.505121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4d68ac4-574d-4bab-9582-8b23fb217a9c · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Certifiable Machine Unlearning for Linear Models

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:57:21.730247Z

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.

Observation 39b53405-65cb-4dd3-bcce-a8c9552d4cfe · inbound

TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations cites this paper.

TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations Certifiable Machine Unlearning for Linear Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:58:47.631177Z

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.

Observation 8dfa23c5-0b5c-4563-85ca-62e4025a376a · inbound

DECAF: De-Clustering for Adaptive Representational Unlearning cites this paper.

DECAF: De-Clustering for Adaptive Representational Unlearning Certifiable Machine Unlearning for Linear Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T23:33:51.026231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.