Paper Citation Record · LEDGER

UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2407.00106.

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

pith.paper-citation-record.v1
2407.00106 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:47:15.329073Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:58:47.220821Z

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 50b3c81f-b5fc-4488-a594-cf0b27da7690 · inbound

Improving LLM Unlearning Robustness via Random Perturbations cites this paper.

Improving LLM Unlearning Robustness via Random Perturbations UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:42:33.443118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34409545-4528-4a6f-8625-d940d11c2c74 · inbound

Position: Adversarial ML for LLMs Is Not Making Any Progress cites this paper.

Position: Adversarial ML for LLMs Is Not Making Any Progress UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T12:47:21.776254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8feae682-7ffa-4ad0-8276-0a9d528e4b60 · inbound

A Lightweight Method to Disrupt Memorized Sequences in LLM cites this paper.

A Lightweight Method to Disrupt Memorized Sequences in LLM UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T20:08:57.474018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b1f053a-be81-4969-aa6a-d73c134f95ac · inbound

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities cites this paper.

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-09T14:47:15.329073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b7b9fe4-c404-4f6c-adc4-0bbb03264506 · inbound

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond cites this paper.

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T19:40:31.595781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d24048b2-12c7-42c5-9e2d-d4380c57cad5 · inbound

LLM Unlearning Should Be Form-Independent cites this paper.

LLM Unlearning Should Be Form-Independent UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:34.794058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f7bb65d-affd-40f1-97b4-2e08bda272ab · inbound

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods cites this paper.

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:37:07.816508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8da58c91-d571-417e-bfad-a647e834fcda · inbound

Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective cites this paper.

Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:29.123898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f4bcc88-8bac-49a7-a45a-b7dafdadc48a · inbound

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction cites this paper.

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 197

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:40.271159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 266af46c-f340-4886-bbfe-1e2ff50b9dbc · inbound

Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection cites this paper.

Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T17:56:10.353899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d13a2d0b-6dd7-47ef-892e-c7d3b823ba60 · inbound

Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models cites this paper.

Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T09:02:58.070315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b0ad20e-ab15-404d-b770-423defedc822 · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:59.274854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d1d836eb-65cc-4785-89a2-cc96e012ce6c · inbound

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning cites this paper.

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:21:05.228819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 63218d4c-abe3-4cbe-b5f2-1b98ae748529 · inbound

SoK: Unlearnability and Unlearning for Model Dememorization cites this paper.

SoK: Unlearnability and Unlearning for Model Dememorization UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 170

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:47:04.237973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2c816a9e-9719-4adc-832a-df0300c692f8 · inbound

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence cites this paper.

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 84

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:32:35.449816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 55f15332-7977-4bb1-aad5-3f1a653837fc · inbound

RepSelect: Robust LLM Unlearning via Representation Selectivity cites this paper.

RepSelect: Robust LLM Unlearning via Representation Selectivity UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:58:47.222613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e3e76e86-f1ea-40a6-8709-31b3b6a28bfc · inbound

PPE-Bench: A Benchmark for Evaluating MLLM Unlearning under Private-Public Entanglement cites this paper.

PPE-Bench: A Benchmark for Evaluating MLLM Unlearning under Private-Public Entanglement UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-12T06:18:42.939955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d07e506-3571-459e-ac17-91fe02b4b98d · inbound

How Context Attribution Handles What the Model Already Knows cites this paper.

How Context Attribution Handles What the Model Already Knows UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI

Reference 242

Resolution: unresolved; no resolver link, observed 2026-07-30T12:03:30.644214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.