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Paper Citation Record · LEDGER

Machine Unlearning: Solutions and Challenges

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.07061.

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

pith.paper-citation-record.v1
2308.07061 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:36:02.508314Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:15:43.712708Z

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 3ebad8de-23f1-4d9c-94e3-2e63a3611d04 · inbound

AdaProb: Efficient Machine Unlearning via Adaptive Probability cites this paper.

AdaProb: Efficient Machine Unlearning via Adaptive Probability Machine Unlearning: Solutions and Challenges

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:15:43.716296Z

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=2026-05-23T17:13:32.169844Z digest=sha256:02fe453eae274b9a20e20b06afcaccd69192d92bfd57552516ed8df734049401

Observation dffef6ff-b69e-4309-8da1-e4801f056805 · inbound

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

How to Protect Models against Adversarial Unlearning? Machine Unlearning: Solutions and Challenges

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:34.714945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:34.714945Z digest=sha256:33cd5049c845518725995462340c62a3f844dfdf6ed4b7bd2d1b05d5bdf92502

Observation a0a20fd5-41d0-499f-b555-a86e04bf5d01 · inbound

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning cites this paper.

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning Machine Unlearning: Solutions and Challenges

Reference 168

Resolution
unresolved
no resolver link, observed 2026-08-16T00:36:02.508314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:36:02.508314Z digest=sha256:fc1411b3edc0b957d1f4e603f850b980d588d67d796ca2b407a85c0f603daacb