Paper Citation Record · LEDGER

Open Problems in Machine Unlearning for AI Safety

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2501.04952.

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

pith.paper-citation-record.v1
2501.04952 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:14.232219Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:07:09.079424Z

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 60ae030b-b32e-451d-82aa-4bfa68f366ee · inbound

Improving LLM Unlearning Robustness via Random Perturbations cites this paper.

Improving LLM Unlearning Robustness via Random Perturbations Open Problems in Machine Unlearning for AI Safety

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:42:33.374070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ff78abf2-6cac-4a21-a43c-05e9bf8b1741 · inbound

Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs cites this paper.

Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs Open Problems in Machine Unlearning for AI Safety

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:31:36.562003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cbae965c-d0c7-4969-b219-24ad96e225dd · inbound

The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It cites this paper.

The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It Open Problems in Machine Unlearning for AI Safety

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:14.232219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 424affdb-564a-45a6-90f9-e5d535904bea · inbound

Model Unlearning via Sparse Autoencoder Subspace Guided Projections cites this paper.

Model Unlearning via Sparse Autoencoder Subspace Guided Projections Open Problems in Machine Unlearning for AI Safety

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T12:28:02.261829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c44d985-63a4-4ab2-98f1-ef23c5ab4aba · inbound

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

Existing Large Language Model Unlearning Evaluations Are Inconclusive Open Problems in Machine Unlearning for AI Safety

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:54.573267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91cdf6c8-4e8b-4ee3-bb68-c4f044edabf0 · inbound

LLM Unlearning Should Be Form-Independent cites this paper.

LLM Unlearning Should Be Form-Independent Open Problems in Machine Unlearning for AI Safety

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:35.279841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2a137df-ba47-48f6-ade7-9f67f15f0b0c · inbound

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

UCD: Unlearning in LLMs via Contrastive Decoding Open Problems in Machine Unlearning for AI Safety

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T04:22:59.810289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e166c7c-cd2f-47c9-8fbf-6251e54a6ddc · 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 Open Problems in Machine Unlearning for AI Safety

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:29:34.908539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e245e26a-c4eb-4edf-82c8-c7a2964b0bd7 · inbound

Minimalist Concept Erasure in Generative Models cites this paper.

Minimalist Concept Erasure in Generative Models Open Problems in Machine Unlearning for AI Safety

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T17:08:57.037562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 547c79dc-8640-4343-9ed9-8337691bd44a · 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 Open Problems in Machine Unlearning for AI Safety

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:39.367947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b678310c-67b5-46fd-87e7-4fc6cf614ef6 · inbound

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories cites this paper.

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories Open Problems in Machine Unlearning for AI Safety

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T18:41:32.801107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2efd3671-9df3-4be6-872d-bf24317afb6b · inbound

MoralityGym: A Benchmark for Evaluating Hierarchical Moral Alignment in Sequential Decision-Making Agents cites this paper.

MoralityGym: A Benchmark for Evaluating Hierarchical Moral Alignment in Sequential Decision-Making Agents Open Problems in Machine Unlearning for AI Safety

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:51:25.918330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a8bda064-b421-4ff2-b829-6ae2fc82a33a · inbound

Label Leakage Attacks in Machine Unlearning: A Parameter and Inversion-Based Approach cites this paper.

Label Leakage Attacks in Machine Unlearning: A Parameter and Inversion-Based Approach Open Problems in Machine Unlearning for AI Safety

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:35:58.951078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bdcdb113-d03f-4cb3-97be-10afe485079b · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? Open Problems in Machine Unlearning for AI Safety

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:59.157355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2bd89f6b-3f50-4ed7-8f00-9ad70cc2f082 · inbound

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification cites this paper.

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification Open Problems in Machine Unlearning for AI Safety

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:21:09.947536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a14e166a-fe26-48ab-96f7-cfc8afd4f59c · inbound

Physical Foundation Models: Fixed hardware implementations of large-scale neural networks cites this paper.

Physical Foundation Models: Fixed hardware implementations of large-scale neural networks Open Problems in Machine Unlearning for AI Safety

Reference 125

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:26:28.452179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef9b06b8-06ae-470c-8450-9c1190c339af · inbound

Unified Safe In-context Image Generation in Multimodal Diffusion Transformers via Restricting Unsafe Information Flows cites this paper.

Unified Safe In-context Image Generation in Multimodal Diffusion Transformers via Restricting Unsafe Information Flows Open Problems in Machine Unlearning for AI Safety

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:09.080835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.