Paper Citation Record · LEDGER

Evaluating Machine Unlearning via Epistemic Uncertainty

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2208.10836.

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

pith.paper-citation-record.v1
2208.10836 v2

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

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:15:29.557071Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T01:13:42.717762Z

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 b932f338-29b1-46cd-b1cf-8fef4e42ed82 · inbound

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation cites this paper.

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 209

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T17:56:23.529038Z

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.

Observation 6b7a1fac-e3b4-4f65-b8b7-af45d6cdc983 · inbound

Machine Unlearning: A Comprehensive Survey cites this paper.

Machine Unlearning: A Comprehensive Survey Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 137

Resolution: verified exact; arxiv_id, observed 2026-05-24T01:13:42.720296Z

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.

Observation af3d5be0-0cc7-4c76-a813-11173eab7a6a · inbound

Targeted Forgetting of Image Subgroups in CLIP Models cites this paper.

Targeted Forgetting of Image Subgroups in CLIP Models Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:29.557071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bbb9168-1884-444a-acef-a8f54d492b16 · inbound

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification cites this paper.

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:37:14.161389Z

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.

Observation 2bb71b2b-31f1-4a20-a282-49ac62acc737 · inbound

Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy cites this paper.

Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:35.309152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e27fd56-4a96-4d59-930d-c1ac1ba4d62b · inbound

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design cites this paper.

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T21:01:26.785208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebf818cc-b5b1-4ab1-a6ed-2bd332ee3199 · inbound

Representation-Guided Parameter-Efficient LLM Unlearning cites this paper.

Representation-Guided Parameter-Efficient LLM Unlearning Evaluating Machine Unlearning via Epistemic Uncertainty

Reference 120

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:19.304021Z

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.