Paper Citation Record · LEDGER

Do Unlearning Methods Remove Information from Language Model Weights?

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2410.08827.

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

pith.paper-citation-record.v1
2410.08827 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:34:31.175467Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:58:47.172516Z

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 6022e9b2-4eb3-4c21-ba42-5f3d265042c7 · inbound

Open Problems in Machine Unlearning for AI Safety cites this paper.

Open Problems in Machine Unlearning for AI Safety Do Unlearning Methods Remove Information from Language Model Weights?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T21:24:10.041831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbb66c9e-8912-4ab8-bb72-08a65b0fc2cf · inbound

Improving LLM Unlearning Robustness via Random Perturbations cites this paper.

Improving LLM Unlearning Robustness via Random Perturbations Do Unlearning Methods Remove Information from Language Model Weights?

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:42:33.420665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f515d96-f150-4a66-87a0-e43671afe57a · inbound

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

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Do Unlearning Methods Remove Information from Language Model Weights?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T14:47:15.078108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e026bcf2-e946-49b4-a975-57a13b8833d5 · 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 Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T19:40:31.549295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 771e45b4-76d7-4b63-95c8-3c9ec0addb26 · inbound

Layered Unlearning for Adversarial Relearning cites this paper.

Layered Unlearning for Adversarial Relearning Do Unlearning Methods Remove Information from Language Model Weights?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T21:34:31.175467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65722495-2614-4feb-bf56-cee0196905b2 · inbound

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

Leveraging Per-Instance Privacy for Machine Unlearning Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:48.810330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4357c90-8381-4d3c-957e-8dd7f44a1ee9 · inbound

Existing Large Language Model Unlearning Evaluations Are Inconclusive cites this paper.

Existing Large Language Model Unlearning Evaluations Are Inconclusive Do Unlearning Methods Remove Information from Language Model Weights?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.186590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 520452ad-db7b-46e6-9ea2-45c31c79b77a · inbound

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack cites this paper.

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack Do Unlearning Methods Remove Information from Language Model Weights?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:52:53.544206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05db6b0c-4c39-45c1-b414-7200b4451c18 · inbound

SoK: Machine Unlearning for Large Language Models cites this paper.

SoK: Machine Unlearning for Large Language Models Do Unlearning Methods Remove Information from Language Model Weights?

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:55.348212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59a716f1-489a-4f4e-beec-8765cfeb6d3f · inbound

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs cites this paper.

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T00:29:35.464938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6676f125-3087-4b2b-b375-58aadbca3d9f · inbound

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap cites this paper.

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap Do Unlearning Methods Remove Information from Language Model Weights?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:01:32.767988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdc8e59c-a7b5-4908-9109-9b292287dc29 · inbound

Step-by-Step Reasoning Attack: Revealing 'Erased' Knowledge in Large Language Models cites this paper.

Step-by-Step Reasoning Attack: Revealing 'Erased' Knowledge in Large Language Models Do Unlearning Methods Remove Information from Language Model Weights?

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:56:31.527816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 103716d5-0a18-4885-94f9-25aec51dad41 · inbound

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning cites this paper.

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning Do Unlearning Methods Remove Information from Language Model Weights?

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:46:17.037187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 997df8a2-e430-44ac-be8c-83f9a2f358c7 · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? Do Unlearning Methods Remove Information from Language Model Weights?

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:59.025013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a03fc6af-3c80-4279-b511-33e0dfa6f309 · inbound

Efficient Unlearning through Maximizing Relearning Convergence Delay cites this paper.

Efficient Unlearning through Maximizing Relearning Convergence Delay Do Unlearning Methods Remove Information from Language Model Weights?

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:30:56.625752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c9f1c6cc-5f16-443f-892a-ff1e2cb8e779 · inbound

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework cites this paper.

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:30:31.236417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c8cd6d89-9ca7-4c67-bddc-61e49fea81f7 · inbound

Robust LLM Unlearning Against Relearning Attacks: The Minor Components in Representations Matter cites this paper.

Robust LLM Unlearning Against Relearning Attacks: The Minor Components in Representations Matter Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:06:59.984664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 097fd0b9-09bc-491b-bbff-04cf8285432b · inbound

Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks cites this paper.

Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks Do Unlearning Methods Remove Information from Language Model Weights?

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:23:53.621029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5acdf056-ca68-4851-92d8-169504e54d27 · inbound

Don't Forget Your Embeddings: Robust Knowledge Erasure via Precise Editing of Embeddings cites this paper.

Don't Forget Your Embeddings: Robust Knowledge Erasure via Precise Editing of Embeddings Do Unlearning Methods Remove Information from Language Model Weights?

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:46:28.906636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7af7c66e-1815-4561-a811-e606838a67bc · inbound

Safe-RULE: Safe Reinforcement UnLEarning cites this paper.

Safe-RULE: Safe Reinforcement UnLEarning Do Unlearning Methods Remove Information from Language Model Weights?

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:07:28.418633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 225954d8-a245-46c7-9a8b-173f989adecf · inbound

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

RepSelect: Robust LLM Unlearning via Representation Selectivity Do Unlearning Methods Remove Information from Language Model Weights?

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:58:47.174073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0ca2d13c-79d0-465b-9c05-4fae6ebf352a · inbound

Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies cites this paper.

Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies Do Unlearning Methods Remove Information from Language Model Weights?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:54:46.398125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1066d879-296c-485a-9662-18f616448947 · inbound

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning cites this paper.

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning Do Unlearning Methods Remove Information from Language Model Weights?

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T14:17:56.759517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.