Paper Citation Record · LEDGER

An Adversarial Perspective on Machine Unlearning for AI Safety

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2409.18025.

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

pith.paper-citation-record.v1
2409.18025 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:47:15.215964Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:58:47.261403Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 6500daed-fcd8-4a20-9963-0a5d92030fd2 · inbound

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

Position: Adversarial ML for LLMs Is Not Making Any Progress An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T12:47:21.702924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52289a63-379a-44f5-b904-0db3406e363f · inbound

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

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-09T14:47:15.215964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 519bc41e-0dcb-4c33-8e15-b3338189d42c · inbound

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

Existing Large Language Model Unlearning Evaluations Are Inconclusive An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:52.023421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc4782b7-50e4-4a7d-848e-1ebc2bfd9f7d · inbound

UCD: Unlearning in LLMs via Contrastive Decoding cites this paper.

UCD: Unlearning in LLMs via Contrastive Decoding An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T04:22:59.866876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 227d9c44-a5c2-40ad-9239-335234cbb5fc · 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 An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:29:36.509811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d69c909-1526-4c78-adb2-25676b41ec5e · 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 An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:01:32.710152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97392904-e4f6-4862-91f5-2e0fae35a55f · 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 An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:56:31.574139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e6a0557-b99b-4b6c-8d9f-c7d264df0dfe · inbound

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests cites this paper.

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:21:33.666080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fae628b5-9d1c-4bf5-9192-f6a92e89689b · inbound

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

Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T17:56:10.334264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dd3bf4c-02b5-4566-b202-6096553fb338 · inbound

Module-Aware Parameter-Efficient Machine Unlearning on Transformers cites this paper.

Module-Aware Parameter-Efficient Machine Unlearning on Transformers An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T17:06:12.524742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dad871f-6b8e-4101-ad54-8d38fdbb88fb · inbound

OFMU: Optimization-Driven Framework for Machine Unlearning cites this paper.

OFMU: Optimization-Driven Framework for Machine Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:06:23.550813Z

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 c161c9ee-07da-4a2f-94fc-7db821b7adb1 · inbound

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

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T10:46:17.069169Z

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 d560bdf5-77c4-4315-ba8b-052c1424b66a · inbound

You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models cites this paper.

You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T21:27:19.292306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0917c547-76f8-40da-a242-9fd8a672c199 · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:59.056339Z

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 54ca28d6-77cb-4f9f-a5f6-b97319187bf0 · inbound

Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning cites this paper.

Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:03:51.502999Z

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 6e472219-aba8-4b68-9a85-3dd88e448cf8 · inbound

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

RepSelect: Robust LLM Unlearning via Representation Selectivity An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:58:47.262968Z

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 550c0e6a-bed8-4bb0-b08a-cdbe9744bf05 · 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 An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 12

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 cf7d06db-0d6e-485a-b07d-5cd5d7123559 · inbound

LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats cites this paper.

LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T10:25:18.726548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d08acd8-1eae-44ce-bed4-16a589addb6e · inbound

Understanding Machine Unlearning Through the Lens of Mode Connectivity cites this paper.

Understanding Machine Unlearning Through the Lens of Mode Connectivity An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-31T23:27:28.047712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation becb4259-c9ee-4a51-b67b-aed74e0e4279 · 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 An Adversarial Perspective on Machine Unlearning for AI Safety

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T18:54:46.552487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.