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Paper Citation Record · LEDGER

A Survey of Machine Unlearning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 66 inbound Pith citation observations for arXiv:2209.02299.

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

pith.paper-citation-record.v1
2209.02299 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 66 of 66 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:13:54.660918Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

67
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 87f7058d-6b21-4a13-8efe-f40b30716c56 · inbound

Cognitive Architectures for Language Agents cites this paper.

Cognitive Architectures for Language Agents A Survey of Machine Unlearning

Reference 55

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arxiv_id, observed 2026-05-16T19:33:44.450604Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fa0ce039-8eb6-4895-83c0-fa27b21933f7 · 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 A Survey of Machine Unlearning

Reference 225

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arxiv_id, observed 2026-05-16T17:56:23.593161Z

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source=arxiv_source observed=2026-05-16T17:56:23.281678Z digest=sha256:162681ecd3d2e5680b279949ef43736a8a7e66640504fcba017ee6f062b04825

Observation 5f0b11c6-2377-44a3-b51a-9bb86746e015 · inbound

Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning cites this paper.

Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning A Survey of Machine Unlearning

Reference 16

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arxiv_id, observed 2026-05-16T22:26:55.061218Z

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Observation 233a7828-8a8a-4e50-a1ad-ffcca9b0da6f · inbound

Machine Unlearning: A Comprehensive Survey cites this paper.

Machine Unlearning: A Comprehensive Survey A Survey of Machine Unlearning

Reference 112

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arxiv_id, observed 2026-05-24T01:13:42.685021Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-24T01:13:26.620111Z digest=sha256:251f9dbe4195eef98b1a1c1b5857a2a7b14d3a9320174f653e8b65ec621d2627

Observation 05843800-ac7b-4516-8142-e516993ca68f · inbound

Towards Certified Unlearning for Deep Neural Networks cites this paper.

Towards Certified Unlearning for Deep Neural Networks A Survey of Machine Unlearning

Reference 12

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arxiv_id, observed 2026-05-23T22:03:30.827693Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T21:59:59.421179Z digest=sha256:bb9ae1042640d97ae865e8ed645934fdfa8078e2a46015e00509afd406ff450b

Observation 13e44458-e59d-4119-a8b5-755f8c82ccf7 · inbound

Verification of Machine Unlearning is Fragile cites this paper.

Verification of Machine Unlearning is Fragile A Survey of Machine Unlearning

Reference 32

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arxiv_id, observed 2026-05-23T22:25:50.530736Z

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source=arxiv_source observed=2026-05-23T22:23:43.259499Z digest=sha256:df40f857c7b2e0ef84e0d84ad98666c38d1a1d9420dc4ee10123166feb49c976

Observation 1b26aca3-9352-48ec-b76e-c684eacfd66a · inbound

Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA cites this paper.

Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA A Survey of Machine Unlearning

Reference 2

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arxiv_id, observed 2026-05-23T17:33:15.768375Z

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source=pdf_text observed=2026-05-23T17:31:22.791816Z digest=sha256:276154fe5565bfee583cc59ee34d3c15e383568b88206f1984039bd7db9a97de

Observation 25722d20-70c2-495e-b9d6-f765e15dd063 · inbound

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents cites this paper.

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents A Survey of Machine Unlearning

Reference 194

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Observation 07831b46-e858-41f6-8575-362bdf8d7a71 · inbound

Verifying Machine Unlearning with Explainable AI cites this paper.

Verifying Machine Unlearning with Explainable AI A Survey of Machine Unlearning

Reference 16

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source=pdf_text observed=2026-08-12T16:37:21.565502Z digest=sha256:3583b6e5ba831760ee8f2d26aafad852e8195514455c11a7378c8c630fc35108

Observation c3cbec9c-2c19-4a74-af5f-eb9dae11dc97 · inbound

Learning to Forget using Hypernetworks cites this paper.

Learning to Forget using Hypernetworks A Survey of Machine Unlearning

Reference 35

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source=pdf_text observed=2026-08-12T05:05:52.334676Z digest=sha256:6b12a15ecde8896e299ee456a8340719fe0d59e3602d5d53c902ff2a551e626a

Observation 8c6ba75c-689d-496f-9c32-f7dfc77504e5 · inbound

A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks cites this paper.

A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks A Survey of Machine Unlearning

Reference 38

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source=arxiv_source observed=2026-08-12T05:06:05.527197Z digest=sha256:50d8ef3c5696dd922ba7e4208d9987b136d54d604be13b47f4e63299d3d63618

Observation 515759b3-bdc5-45b8-85fc-42d468adee47 · inbound

Siamese Machine Unlearning with Knowledge Vaporization and Concentration cites this paper.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration A Survey of Machine Unlearning

Reference 23

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source=pdf_text observed=2026-08-12T04:41:55.366747Z digest=sha256:f61086b619c5b037d54ad0c67c73cc019705d753eaa05fe9bbe508a96a38dd73

Observation 2c02c80b-fdef-40cf-9155-9bf268c4c0f9 · inbound

Toward Efficient Data-Free Unlearning cites this paper.

Toward Efficient Data-Free Unlearning A Survey of Machine Unlearning

Reference 26

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source=arxiv_source observed=2026-08-11T12:53:59.053824Z digest=sha256:b4ec35eb085ed3c6c94b604abfca796b5a390054aa3945423b289dc8334887c9

Observation 11087bbe-bfd5-4c87-ae0a-623faf5bec92 · inbound

Effective and secure federated online learning to rank cites this paper.

Effective and secure federated online learning to rank A Survey of Machine Unlearning

Reference 104

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source=pdf_text observed=2026-08-11T01:03:35.047524Z digest=sha256:35473e9c3fae209032f9c545c42c031a3662a277339884f15a53d0e4a6a836f7

Observation 860676fe-f804-4626-9fbf-632dacd16e3a · inbound

Unraveling Token Prediction Refinement and Identifying Essential Layers in Language Models cites this paper.

Unraveling Token Prediction Refinement and Identifying Essential Layers in Language Models A Survey of Machine Unlearning

Reference 22

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source=pdf_text observed=2026-08-10T14:43:14.782996Z digest=sha256:8fe49178dd0e0917632b4d5d86fe687607e1883cf121c7951b1b051962293c7d

Observation 5b452712-0291-4e93-acbe-e2ba7f13e187 · inbound

Technology Mapping with Large Language Models cites this paper.

Technology Mapping with Large Language Models A Survey of Machine Unlearning

Reference 44

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source=pdf_text observed=2026-08-10T14:41:50.030466Z digest=sha256:994d69d8eab3b2c413d54fe8172be6559471e334cf6f33f3e31ca06d77971067

Observation 74e58149-d871-4205-9daa-40b3e79e7104 · inbound

Hypergraph Diffusion for High-Order Recommender Systems cites this paper.

Hypergraph Diffusion for High-Order Recommender Systems A Survey of Machine Unlearning

Reference 11

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source=pdf_text observed=2026-08-10T11:14:29.680226Z digest=sha256:c63b6ad535bca97ab89d46b20396781850c398003df946eec8382b8ea81b3d3d

Observation 51ef4367-990e-455e-9b9c-5ce6da5793ff · inbound

Improving LLM Unlearning Robustness via Random Perturbations cites this paper.

Improving LLM Unlearning Robustness via Random Perturbations A Survey of Machine Unlearning

Reference 25

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arxiv_id, observed 2026-05-23T04:42:33.305756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 08cbefa3-84cd-47cb-97ea-d8755d0f4773 · inbound

Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data cites this paper.

Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data A Survey of Machine Unlearning

Reference 2007

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source=pdf_text observed=2026-08-09T14:50:58.712354Z digest=sha256:f49247919179f81524ba750b56b60263074291f51e944ad992bbdeb475928425

Observation 3d704dd4-e0e0-4277-b21e-7c3686a20eee · inbound

Model-Free Counterfactual Subset Selection at Scale cites this paper.

Model-Free Counterfactual Subset Selection at Scale A Survey of Machine Unlearning

Reference 52

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source=pdf_text observed=2026-08-08T05:38:45.730193Z digest=sha256:292fe540c0d12d73469f9564ad2c20acfe2168c6810516a558ca51c5d198d602

Observation 19b95aba-8348-46ea-aa17-12b886cb8095 · inbound

The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models cites this paper.

The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models A Survey of Machine Unlearning

Reference 14

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source=pdf_text observed=2026-08-16T05:13:54.660918Z digest=sha256:39f4b1056249aa26d20c170f658114c92a7542edb2ed1c173aee897a73570e23

Observation 4b4df907-0eea-4b24-a0f3-6c7733b375f0 · inbound

Memory-Efficient Distributed Unlearning cites this paper.

Memory-Efficient Distributed Unlearning A Survey of Machine Unlearning

Reference 11

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source=pdf_text observed=2026-08-15T23:58:55.102064Z digest=sha256:7f88cf7234d5927fd2042ca1d0424f30234122db258417ccc14df5e2ece30221

Observation 569a61bb-f196-4e5a-9017-b074babe40d4 · inbound

Efficient Machine Unlearning by Model Splitting and Core Sample Selection cites this paper.

Efficient Machine Unlearning by Model Splitting and Core Sample Selection A Survey of Machine Unlearning

Reference 14

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source=pdf_text observed=2026-08-15T22:36:06.599433Z digest=sha256:15abe90cce36374666d966c3db5b55cc7748693ef0d3763aefc582f20d0891cf

Observation 2285bb4b-298d-41f4-a0aa-dc8ae334d855 · inbound

Certified Data Removal Under High-dimensional Settings cites this paper.

Certified Data Removal Under High-dimensional Settings A Survey of Machine Unlearning

Reference 46

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source=arxiv_source observed=2026-08-15T22:17:39.720183Z digest=sha256:aa85c381244c61c896fab0893dfe4c900ac6bcda7b7a539a8909d3952642107e

Observation 0a028518-fb94-4a51-a526-5643ba6aba3a · inbound

Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning cites this paper.

Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning A Survey of Machine Unlearning

Reference 31

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source=pdf_text observed=2026-08-15T22:11:08.596732Z digest=sha256:6375ea72cfe232574f78693303d8d762679941f771c6536702782475a8011db5

Observation 10a0dbf7-64e1-400a-be46-1fed54dfe90b · inbound

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing cites this paper.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A Survey of Machine Unlearning

Reference 54

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source=pdf_text observed=2026-08-15T21:31:25.487991Z digest=sha256:ba64231a86809fd83ee0e43c9271a5891a142717599bf9421dad3d46317b4c31

Observation 6f60bf06-fc5d-4eb3-827a-0127efebb6ea · inbound

DUSK: Do Not Unlearn Shared Knowledge cites this paper.

DUSK: Do Not Unlearn Shared Knowledge A Survey of Machine Unlearning

Reference 47

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source=pdf_text observed=2026-08-07T15:26:24.146987Z digest=sha256:276dbaba159496b7758e95a3c17d6bb5913948bbd4f84bb640b2e3add5d5bdcc

Observation 3d54c82b-1378-4cd6-be8b-7b6ebf62bd50 · inbound

Towards Machine Unlearning for Paralinguistic Speech Processing cites this paper.

Towards Machine Unlearning for Paralinguistic Speech Processing A Survey of Machine Unlearning

Reference 12

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source=pdf_text observed=2026-08-07T11:30:04.121573Z digest=sha256:a253a52192c57cba8d2e2705691e0331439f4345a96978e064c0cbb246954672

Observation c43b6982-a793-4316-a584-b5e715dd4ef7 · inbound

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery cites this paper.

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery A Survey of Machine Unlearning

Reference 46

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source=pdf_text observed=2026-08-07T10:44:40.250400Z digest=sha256:a63365bd66bbdfe7652d0774e078d9b9bab7fb73c29852b69cc97c3ab009c292

Observation 16045cde-a8a6-422b-87e1-6c40826da794 · inbound

Certified Unlearning for Neural Networks cites this paper.

Certified Unlearning for Neural Networks A Survey of Machine Unlearning

Reference 30

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source=arxiv_source observed=2026-08-07T06:00:41.366497Z digest=sha256:3f2b76c9000dfe56957e4627f8fbb5b7e0f489fdf9735b12b865cb7a5452bd16

Observation 4bff8cbd-0953-40ba-9515-f7c8f7be6fcc · inbound

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

UCD: Unlearning in LLMs via Contrastive Decoding A Survey of Machine Unlearning

Reference 23

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source=pdf_text observed=2026-08-07T04:22:59.875845Z digest=sha256:d9b56351ded1885cf4185d525d6b0b63121d2b3dc88e952514d7214f1d1b4a81

Observation a1cf27e8-f4db-41c4-8e6c-ef682a7b303c · inbound

The Space Complexity of Learning-Unlearning Algorithms cites this paper.

The Space Complexity of Learning-Unlearning Algorithms A Survey of Machine Unlearning

Reference 81

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source=arxiv_source observed=2026-08-07T00:53:51.385970Z digest=sha256:3fe47a1a9ed0fa0d8f1f2617e04c527ad367236f39d14d663412d1bf316e1e13

Observation 1b3194d7-f479-4c2d-82fb-c80ca1b40fbd · inbound

Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble cites this paper.

Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble A Survey of Machine Unlearning

Reference 38

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source=pdf_text observed=2026-08-07T00:30:35.217945Z digest=sha256:c9cff2e2c5e763d323fbf9681132e88960e4b5099265b0d434bd570b6cb9ec72

Observation ecf25c02-d2ed-4477-9458-caec2a189a76 · 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 A Survey of Machine Unlearning

Reference 18

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source=pdf_text observed=2026-08-07T00:29:37.032784Z digest=sha256:d4ae7e0d3dcda9514476035b46f3c2030d800e85200d66261864350a6214f8a5

Observation c2926b40-36db-440f-bbd6-cf0e4dffe47f · inbound

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

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification A Survey of Machine Unlearning

Reference 82

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arxiv_id, observed 2026-05-19T09:37:14.096946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-19T09:35:00.520860Z digest=sha256:27e9b5ecb5056b6055cd70676e5f0d032768f7c478e05800243710e89015ca70

Observation 3bfd1dc0-b989-46fa-998a-1b0ee199bd14 · inbound

A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset cites this paper.

A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset A Survey of Machine Unlearning

Reference 98

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arxiv_id, observed 2026-05-19T08:22:11.096584Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-19T08:18:48.936867Z digest=sha256:4b3261632b7163771d12301e335ed5a2443b8ae97dc5cd08a4d3508f5c1b768b

Observation 4dc3cc84-9564-4c84-a744-08ac86e496f6 · inbound

How to Protect Models against Adversarial Unlearning? cites this paper.

How to Protect Models against Adversarial Unlearning? A Survey of Machine Unlearning

Reference 39

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source=pdf_text observed=2026-08-06T17:26:34.231342Z digest=sha256:00e430a20521ad191717c2ca44bf686b7a43733f82ce83fd78d352cf09cbf483

Observation e9128333-475b-44e2-8e06-7ba4ce92964c · 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 A Survey of Machine Unlearning

Reference 45

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source=pdf_text observed=2026-08-06T17:21:33.704900Z digest=sha256:a1cde084ea194e8b0eddb2172b8cb3b9e4edf1583c3f44af8b47efb66271e622

Observation 899124f5-095c-4f35-8671-4d86deff3855 · inbound

Machine Unlearning for Streaming Forgetting cites this paper.

Machine Unlearning for Streaming Forgetting A Survey of Machine Unlearning

Reference 40

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source=pdf_text observed=2026-08-06T15:43:55.837397Z digest=sha256:5669b0ffc670e030949df91b9dd01b7b00193de8ef48f23d481f1cdc293e6e96

Observation 6bb3c4ad-6370-46cb-9bb1-23800bc3932a · inbound

RecPS: Privacy Risk Scoring for Recommender Systems cites this paper.

RecPS: Privacy Risk Scoring for Recommender Systems A Survey of Machine Unlearning

Reference 23

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source=pdf_text observed=2026-08-15T18:18:15.371999Z digest=sha256:e3528c8849ac325dd8f8f70cc51559d95cf4ad22263a6ca5442fe16d8bb40c47

Observation 031fc26f-6e8b-4429-ab15-36caca0bd9de · inbound

Unlearning of Knowledge Graph Embedding via Preference Optimization cites this paper.

Unlearning of Knowledge Graph Embedding via Preference Optimization A Survey of Machine Unlearning

Reference 22

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no resolver link, observed 2026-08-15T17:46:03.111419Z

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source=pdf_text observed=2026-08-15T17:46:03.111419Z digest=sha256:1ce9c3f248b4471c988c9e81018c369f974a24a8bc6b01e9d95b3b320b4b43d7

Observation 5c437d1d-b040-413e-83c9-4950825f93fc · inbound

Envisioning Generative Artificial Intelligence in Cartography and Mapmaking cites this paper.

Envisioning Generative Artificial Intelligence in Cartography and Mapmaking A Survey of Machine Unlearning

Reference 34

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no resolver link, observed 2026-08-15T17:32:49.597889Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:32:49.597889Z digest=sha256:05f9af34d1b461fb59f5ce80a462d8c3179a00485d46c000b1834ac3c8ee71f1

Observation 1e61de2b-4125-4027-9618-95ef9d8df118 · 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 A Survey of Machine Unlearning

Reference 2

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source=pdf_text observed=2026-08-05T21:01:26.724161Z digest=sha256:a9b21a9cda3ad9600bbdab91495791d82afc750215ef0af3565b70264ce78c56

Observation d655cced-50ce-4684-916d-9bd71fc31f0f · inbound

Auditing Approximate Machine Unlearning for Differentially Private Models cites this paper.

Auditing Approximate Machine Unlearning for Differentially Private Models A Survey of Machine Unlearning

Reference 26

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no resolver link, observed 2026-08-05T16:22:55.059845Z

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source=pdf_text observed=2026-08-05T16:22:55.059845Z digest=sha256:4bcded9fb0535c397957276e2ea04390591e970c222ee2be95bd8d161a183e43

Observation 9c7d79b6-c22c-43dd-88bc-ab8c7d1299fc · inbound

Graph Unlearning: Efficient Node Removal in Graph Neural Networks cites this paper.

Graph Unlearning: Efficient Node Removal in Graph Neural Networks A Survey of Machine Unlearning

Reference 30

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source=pdf_text observed=2026-08-15T16:31:50.145702Z digest=sha256:03f62ba730d61108ed22a1dee8c5179a039cc8bcdcbd4da0fa9822ccd4af3920

Observation de9b93d3-a2b9-4a7a-95e7-b39c4115a8a4 · inbound

The Measure of Deception: An Analysis of Data Forging in Machine Unlearning cites this paper.

The Measure of Deception: An Analysis of Data Forging in Machine Unlearning A Survey of Machine Unlearning

Reference 21

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verified exact
arxiv_id, observed 2026-05-18T17:42:47.381428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T17:40:20.637543Z digest=sha256:74cf0609df2fce320ef593a1fc21038bb3ee7a040a91522219cb11b3621eb3cd

Observation 8ad36c83-7027-4ce1-bd45-4a21c8f3cdf0 · inbound

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning cites this paper.

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning A Survey of Machine Unlearning

Reference 15

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no resolver link, observed 2026-08-04T11:27:21.659846Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T11:27:21.659846Z digest=sha256:cd91352e11b25dd3d04f7b1805eba7aa0cda0cc34aa1b97556e5ce3b6552f2b5

Observation 3b53cb84-2fb3-4ec0-9c7f-647e33159785 · inbound

Sequential Subspace Noise Injection Prevents Accuracy Collapse in Certified Unlearning cites this paper.

Sequential Subspace Noise Injection Prevents Accuracy Collapse in Certified Unlearning A Survey of Machine Unlearning

Reference 2

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no resolver link, observed 2026-08-03T11:54:00.531779Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-03T11:54:00.531779Z digest=sha256:18003cf7fe55b585e1638814807d3103e25f175cb2f0acba9133a856132ede22

Observation d0262184-fde4-478a-a7ca-69d87b64ceb7 · inbound

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking cites this paper.

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking A Survey of Machine Unlearning

Reference 10

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verified exact
arxiv_id, observed 2026-05-21T17:14:16.709173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-21T17:12:33.892879Z digest=sha256:f9c0d9a1562d0e4806d50053b2d33f4687425bc7331d229eb53f3a20adcfd991

Observation 30d6ff40-aee3-4d08-8871-2a772226a895 · inbound

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning cites this paper.

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning A Survey of Machine Unlearning

Reference 2025

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source=pdf_text observed=2026-08-03T06:35:42.937561Z digest=sha256:1b3a050a46807d6a9968f492226cb8f2487f666a132eaab9eff6fd9ffcc436d9

Observation 2f488c9b-4442-46db-895e-813cf26d687d · inbound

Is your algorithm unlearning or untraining? cites this paper.

Is your algorithm unlearning or untraining? A Survey of Machine Unlearning

Reference 23

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verified exact
arxiv_id, observed 2026-05-11T05:30:59.091610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T18:06:08.962042Z digest=sha256:301ece4fad57bf5237fc1410ba2c1aa574ae4951176e9983de032bb6173fa4f1

Observation ea9c61c9-e3d3-4ae1-802c-4562b0a5603f · inbound

Efficient Unlearning through Maximizing Relearning Convergence Delay cites this paper.

Efficient Unlearning through Maximizing Relearning Convergence Delay A Survey of Machine Unlearning

Reference 40

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verified exact
arxiv_id, observed 2026-05-11T08:26:02.126798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T16:37:24.974659Z digest=sha256:51f7b1283342545ab3f6e7f1b9a64dee6f2831a5744d87b8257ef266f797fcf2

Observation 029e2b83-f3d3-4829-b3f0-242669f1fb0e · inbound

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

Representation-Guided Parameter-Efficient LLM Unlearning A Survey of Machine Unlearning

Reference 170

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arxiv_id, observed 2026-05-10T06:06:19.238002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-10T06:01:46.885030Z digest=sha256:a3e85ab75b343c70b18ea4ae2be8e02143d0b4f6aa13a654add5b405e724cbd6

Observation 55aace70-1b85-45f7-8716-daad0026da0a · inbound

Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning cites this paper.

Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning A Survey of Machine Unlearning

Reference 11

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verified exact
arxiv_id, observed 2026-05-11T15:36:06.628672Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T19:39:15.279115Z digest=sha256:f702443de3390beed229fb714a7fa615c71cee7d138274ed1540a43f646de4e3

Observation 76563ab7-f778-46a2-acb0-f5b095739400 · inbound

LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning cites this paper.

LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning A Survey of Machine Unlearning

Reference 37

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arxiv_id, observed 2026-05-11T16:06:22.709970Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T18:44:05.775332Z digest=sha256:1a343aa4accd6c610d950e6523429dc419b8024f3c9d9e8b929d996f795d4e94

Observation 5b909d24-14da-4cc0-9f5b-6350ea53c0e1 · inbound

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set cites this paper.

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set A Survey of Machine Unlearning

Reference 28

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verified exact
arxiv_id, observed 2026-05-11T16:11:08.422074Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T18:36:21.189195Z digest=sha256:3b827f50609e0a74eed74b61ce25a1f3826aba744e3d5f435f186360f2cd9661

Observation bbfd3178-f5e8-4fc0-957d-3b77679e9460 · inbound

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set cites this paper.

Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set A Survey of Machine Unlearning

Reference 28

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verified exact
arxiv_id, observed 2026-07-01T07:35:28.966420Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-01T07:30:02.278335Z digest=sha256:b8bb06afaef69e9e88a0717e5ef38bf8dfce1903c75bd63f88b105250a78c081

Observation 0ebff3d4-484e-45c0-ad47-46d492a4b47b · inbound

Exact Unlearning from Proxies Induces Closeness Guarantees on Approximate Unlearning cites this paper.

Exact Unlearning from Proxies Induces Closeness Guarantees on Approximate Unlearning A Survey of Machine Unlearning

Reference 20

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arxiv_id, observed 2026-05-12T07:16:29.654347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-12T03:33:03.867735Z digest=sha256:c57708ac4b227a9331445e39ca770987988337a83cfd266a374395492177ca84

Observation b2820ef4-1245-4ca6-a90e-b35fe4707ac5 · inbound

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces cites this paper.

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces A Survey of Machine Unlearning

Reference 264

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arxiv_id, observed 2026-05-14T20:17:55.456533Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-14T20:17:01.224864Z digest=sha256:c1d61833e91f4894ae396b20b63c633dfaf4e19e431c6665a61fe4ee8bbbeb8c

Observation 50f88544-41c4-4a76-8530-1214203f75fe · inbound

Inducing Artificial Uncertainty in Language Models cites this paper.

Inducing Artificial Uncertainty in Language Models A Survey of Machine Unlearning

Reference 26

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arxiv_id, observed 2026-05-14T20:12:55.532482Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-14T20:11:44.878211Z digest=sha256:1de268d1bf0943357aadc7f96a01d9c1930620b63a3fe637ccd618f1c24adc34

Observation 23f2d5c5-b87c-4ce2-9cc3-e2d1b9ccfe2a · 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 A Survey of Machine Unlearning

Reference 22

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T06:18:42.939955Z digest=sha256:8eb4a5d614309b2b5409eface63d7a260979f9721cfe8f3adb336e2f293dcfde

Observation c520f5ea-e749-4cc4-ac76-52ed112c4d5a · inbound

POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking cites this paper.

POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking A Survey of Machine Unlearning

Reference 11

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local_arxiv, observed 2026-07-11T00:27:50.536199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-11T00:23:30.377235Z digest=sha256:a93476aa2e89dddf4af4ade02f83f9294d99410a20230c3d5ad8767a988e0d89

Observation 1c4e83d2-82e0-4b60-8bf4-3716a429421f · inbound

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks cites this paper.

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks A Survey of Machine Unlearning

Reference 65

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local_arxiv, observed 2026-07-10T15:47:23.283798Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-10T15:38:58.361411Z digest=sha256:f42951d15892132b4fccac4d866c48abb8bf90d53db764e08b695fe13076f09f

Observation 04950356-b81b-4b3a-a91f-8eccbf16b081 · inbound

Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning cites this paper.

Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning A Survey of Machine Unlearning

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T07:47:11.843091Z digest=sha256:8db6e3e7962cd3f84a4cfeb7e5647dca8ed27a067ffe81fca6f606ef30a65f3c

Observation 3eeebce0-7065-43ba-8a9b-fad81bb182cc · inbound

DECAF: De-Clustering for Adaptive Representational Unlearning cites this paper.

DECAF: De-Clustering for Adaptive Representational Unlearning A Survey of Machine Unlearning

Reference 27

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no resolver link, observed 2026-07-31T23:33:51.371798Z

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source=arxiv_source observed=2026-07-31T23:33:51.371798Z digest=sha256:30fe31055901c9eacc3f0c1e2317437feaf4b966b2ceb18406e5ae54d55f8650

Observation 9ab6abdc-541c-4fee-92a5-a3540fafe80d · inbound

LU-500: A Logo Benchmark for Concept Unlearning cites this paper.

LU-500: A Logo Benchmark for Concept Unlearning A Survey of Machine Unlearning

Reference 6

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source=pdf_text observed=2026-07-31T23:06:19.152638Z digest=sha256:dc1e832e17acd040f2d86d4f0721a1629b917f05d41d202c42987843a0e4274e