Paper Citation Record · LEDGER

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2507.09786.

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

pith.paper-citation-record.v1
2507.09786 v3

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:17.784536Z

measured 32 of 32 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy23
unresolved8
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfd230d8-79c2-4c18-98e8-8adcda7e0511 · outbound

This paper cites Machine unlearning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Machine unlearning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.292170Z

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

Observation 7d1de46a-e130-4435-8a48-eb64ae1e432d · outbound

This paper cites Towards making systems for- get with machine unlearning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Towards making systems for- get with machine unlearning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.279232Z

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Observation a38dfa9c-32cf-4e8e-970d-99e83befec09 · outbound

This paper cites Membership inference attacks from first principles.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Membership inference attacks from first principles

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.265937Z

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Observation f2f5ca84-e387-44cd-9cae-19f06f7fc976 · outbound

This paper cites Dataset distillation by matching training trajectories.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset distillation by matching training trajectories

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.252199Z

Source-reported events for the cited work

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Observation 4499a1f1-a257-420b-a4e1-092c24b917b8 · outbound

This paper cites Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.238141Z

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Observation 0db3e855-1450-4c69-b57b-ecf95c761239 · outbound

This paper cites Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.225299Z

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 8411774b-af62-41c1-89e6-de4b283711ef · outbound

This paper cites Quickdrop: Ef- ficient federated unlearning via synthetic data generation.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Quickdrop: Ef- ficient federated unlearning via synthetic data generation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.213326Z

Source-reported events for the cited work

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Observation 17c992ec-d6cc-41e9-8149-8f5986a01afa · outbound

This paper cites Making ai forget you: Data deletion in ma- chine learning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Making ai forget you: Data deletion in ma- chine learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.199436Z

Source-reported events for the cited work

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Observation 09748e89-2aa2-41f9-9515-fca662c9a1a2 · outbound

This paper cites Eternal sunshine of the spotless net: Selective forgetting in deep networks.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.186501Z

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 8c29439d-8b25-47e5-8339-3ecfb402fb10 · outbound

This paper cites Amne- siac machine learning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Amne- siac machine learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.172239Z

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 a5f48d7f-e39d-40b8-b9c2-d0adaecc95c0 · outbound

This paper cites Certified Data Removal from Machine Learning Models.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Certified Data Removal from Machine Learning Models

Reference 11

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Source-reported events for the cited work

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Observation 821c83b9-dc60-4340-9c11-126bf449e551 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Batch normalization: Accelerating deep network training by reducing internal co- variate shift

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.156623Z

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 51018121-bec9-434d-b9b8-70cb5a807afa · outbound

This paper cites Model Sparsity Can Simplify Machine Unlearning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Model Sparsity Can Simplify Machine Unlearning

Reference 13

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Source-reported events for the cited work

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Observation c073debf-3edb-4356-9262-fc38b79cd16a · outbound

This paper cites Dataset condensation via efficient synthetic- data parameterization.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset condensation via efficient synthetic- data parameterization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.143360Z

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 2b564ceb-a819-47cf-abce-bc7ff896fdf6 · outbound

This paper cites Towards unbounded machine unlearn- ing.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Towards unbounded machine unlearn- ing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.128428Z

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 bddeec3a-12ea-4109-bc0e-6fdaa6dd683e · outbound

This paper cites Distillation robustifies unlearning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Distillation robustifies unlearning

Reference 16

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Source-reported events for the cited work

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Observation 42a685a7-616f-4815-b041-83a0ef65b06f · outbound

This paper cites TCGU: Data-centric Graph Unlearning based on Transferable Condensation.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster TCGU: Data-centric Graph Unlearning based on Transferable Condensation

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:54:17.866147Z

Source-reported events for the cited work

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Observation 73cf9e6b-2423-452b-ad9f-18f31737c8ad · outbound

This paper cites Mubox: A critical evaluation framework of deep machine unlearning [systematization of knowledge paper].

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Mubox: A critical evaluation framework of deep machine unlearning [systematization of knowledge paper]

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.112976Z

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 c28edc61-be2e-4b39-956b-8f0a45cb14b2 · outbound

This paper cites Certifiable Machine Unlearning for Linear Models.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Certifiable Machine Unlearning for Linear Models

Reference 19

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Source-reported events for the cited work

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Observation 525bc1d4-68b3-450b-bfaa-923abd09f1d7 · outbound

This paper cites Dataset distillation with infinitely wide convolutional networks.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset distillation with infinitely wide convolutional networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.099676Z

Source-reported events for the cited work

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Observation 41b4c3c3-46d3-4d96-9873-d3f43038b049 · outbound

This paper cites Pruning neural networks without any data by iter- atively conserving synaptic flow.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Pruning neural networks without any data by iter- atively conserving synaptic flow

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.086990Z

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 67d9e63e-9e4f-4ecc-a3d7-a1f989466e5d · outbound

This paper cites Transfor- mation of arbitrary distributions to the normal distribution with application to eeg test–retest reliability.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Transfor- mation of arbitrary distributions to the normal distribution with application to eeg test–retest reliability

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.073172Z

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 3bde29b3-10fe-4a09-993f-273700620911 · outbound

This paper cites Emphasizing dis- criminative features for dataset distillation in complex sce- narios.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Emphasizing dis- criminative features for dataset distillation in complex sce- narios

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.059421Z

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 fc863b3a-9a01-4d65-9b1f-c776007b5cc8 · outbound

This paper cites Dataset Distillation.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset Distillation

Reference 24

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Source-reported events for the cited work

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Observation 02ce1109-a11b-4a6c-9107-c7e33bd4f378 · outbound

This paper cites Machine Unlearning of Features and Labels.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Machine Unlearning of Features and Labels

Reference 25

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Source-reported events for the cited work

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Observation c7bc566b-6f0a-4329-a2c8-93daa22924b6 · outbound

This paper cites Delta- grad: Rapid retraining of machine learning models.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Delta- grad: Rapid retraining of machine learning models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.758511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81afb98a-0dcb-4bc6-84cb-6972dc2f225a · outbound

This paper cites Arcane: An efficient architecture for ex- act machine unlearning.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Arcane: An efficient architecture for ex- act machine unlearning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.036441Z

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 56bd069f-73e4-4801-9082-0fb07292227f · outbound

This paper cites Dataset condensation with differ- entiable siamese augmentation.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset condensation with differ- entiable siamese augmentation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.021708Z

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 62326631-a588-48df-8dbc-c5e5a9164586 · outbound

This paper cites Dataset condensation with dis- tribution matching.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset condensation with dis- tribution matching

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.007005Z

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 0bcd7685-6ab4-4d37-9c56-2b9dfad46ea0 · outbound

This paper cites Dataset Condensation with Gradient Matching.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Dataset Condensation with Gradient Matching

Reference 30

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Source-reported events for the cited work

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Observation 2e17e044-efa0-42d7-a688-54d0b12f5a0c · outbound

This paper cites Im- proved distribution matching for dataset condensation.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Im- proved distribution matching for dataset condensation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:17.991919Z

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 2b0da8e1-e599-47f6-ae18-7882a278f956 · outbound

This paper cites Decoupled distillation to erase: A general unlearning method for any class-centric tasks.

Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster Decoupled distillation to erase: A general unlearning method for any class-centric tasks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:17.978360Z

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.

Pith citing papers

No inbound Pith citation observations are available.