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Paper Citation Record · LEDGER

Towards Source-Free Machine Unlearning

As of 5 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2508.15127.

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

pith.paper-citation-record.v1
2508.15127 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:12:30.843082Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90884094-d452-49ef-8de7-8e85e1ff86c1 · outbound

This paper cites Machine unlearning.

Towards Source-Free Machine Unlearning Machine unlearning

Reference 1

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Observation 084de97e-4bfa-45d6-89cb-3d25d3474a94 · outbound

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

Towards Source-Free Machine Unlearning Towards making systems for- get with machine unlearning

Reference 2

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Observation fab4982f-9d05-453e-b89b-60b11171345c · outbound

This paper cites Learning to unlearn: Instance-wise unlearning for pre-trained classifiers.

Towards Source-Free Machine Unlearning Learning to unlearn: Instance-wise unlearning for pre-trained classifiers

Reference 3

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Observation a8d5ef63-2f87-4787-b9c8-6a57a20d32d2 · outbound

This paper cites Fast model debias with machine un- learning.

Towards Source-Free Machine Unlearning Fast model debias with machine un- learning

Reference 4

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Observation 803a9be5-dd2a-4d11-9f89-289f9556c15e · outbound

This paper cites Zero-shot machine unlearning.

Towards Source-Free Machine Unlearning Zero-shot machine unlearning

Reference 5

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Source-reported events for the cited work

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Observation a1104843-0b5e-418a-a521-90b167c47c2a · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Towards Source-Free Machine Unlearning Imagenet: A large-scale hierarchical image database

Reference 6

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Observation c00db08e-a1a6-4587-b618-6dd9ddd2c2c1 · outbound

This paper cites Safe: Machine unlearning with shard graphs.

Towards Source-Free Machine Unlearning Safe: Machine unlearning with shard graphs

Reference 7

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Observation fd30b1b5-b516-47a9-b008-a3e943b5f13b · outbound

This paper cites The algorithmic foun- dations of differential privacy.

Towards Source-Free Machine Unlearning The algorithmic foun- dations of differential privacy

Reference 8

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Source-reported events for the cited work

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Observation efc7158b-65d0-442a-ab0a-dffe5c811e9b · outbound

This paper cites An Information Theoretic Approach to Machine Unlearning.

Towards Source-Free Machine Unlearning An Information Theoretic Approach to Machine Unlearning

Reference 9

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Source-reported events for the cited work

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Observation 3525d043-9a5d-4a8c-aa5e-e65c57349c75 · outbound

This paper cites Erasing concepts from diffusion models.

Towards Source-Free Machine Unlearning Erasing concepts from diffusion models

Reference 10

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Source-reported events for the cited work

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Observation 8e0a01cc-3890-43d5-a1b0-30cb9b0b9197 · outbound

This paper cites General data protection regulation.

Towards Source-Free Machine Unlearning General data protection regulation

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 0e412f62-05f1-4166-9cf0-782844bc750b · outbound

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

Towards Source-Free Machine Unlearning Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 12

Resolution
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Source-reported events for the cited work

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Observation a6c6da3d-05ec-4885-90ca-593bd9bd23e7 · outbound

This paper cites Mixed-privacy for- getting in deep networks.

Towards Source-Free Machine Unlearning Mixed-privacy for- getting in deep networks

Reference 13

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Source-reported events for the cited work

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Observation bfeb0051-6235-4a5f-ab86-0c957a2f2b55 · outbound

This paper cites Caltech-256 object category dataset.

Towards Source-Free Machine Unlearning Caltech-256 object category dataset

Reference 14

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Observation c0e87ec5-5006-4de1-b4d1-da6b1da22b62 · outbound

This paper cites Certified data removal from machine learning models.

Towards Source-Free Machine Unlearning Certified data removal from machine learning models

Reference 15

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Source-reported events for the cited work

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Observation 46dccf75-c2fa-4b79-a3bf-28fc22c5fa90 · outbound

This paper cites Deep residual learning for image recognition.

Towards Source-Free Machine Unlearning Deep residual learning for image recognition

Reference 16

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Source-reported events for the cited work

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Observation ba9fdc99-ccb7-47e5-8fbc-0744fd91d8b1 · outbound

This paper cites Neu- ral tangent kernel: Convergence and generalization in neural networks.

Towards Source-Free Machine Unlearning Neu- ral tangent kernel: Convergence and generalization in neural networks

Reference 17

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Source-reported events for the cited work

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Observation c660028e-2018-4eca-99c5-67c76b61a041 · outbound

This paper cites Novel dataset for fine-grained image categorization.

Towards Source-Free Machine Unlearning Novel dataset for fine-grained image categorization

Reference 18

Resolution
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Source-reported events for the cited work

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Observation ca510a78-6461-446d-8152-184d9451ba98 · outbound

This paper cites Learning multiple layers of features from tiny images.

Towards Source-Free Machine Unlearning Learning multiple layers of features from tiny images

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 21608175-53bb-453a-a3b2-3c3b2de46efb · outbound

This paper cites Towards unbounded machine unlearn- ing.

Towards Source-Free Machine Unlearning Towards unbounded machine unlearn- ing

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 78ae0ef7-c933-466f-8328-8c095154e6c4 · outbound

This paper cites Machine Unlearning for Image-to-Image Generative Models.

Towards Source-Free Machine Unlearning Machine Unlearning for Image-to-Image Generative Models

Reference 21

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Source-reported events for the cited work

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Observation 918c0a65-c5ef-46ef-a5c0-67681e1d4f33 · outbound

This paper cites Enhanced Convolutional Neural Tangent Kernels.

Towards Source-Free Machine Unlearning Enhanced Convolutional Neural Tangent Kernels

Reference 22

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Source-reported events for the cited work

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Observation 43ec90fd-4166-42f0-8a4f-223aec517e06 · outbound

This paper cites Do we really need to access the source data? source hypothesis transfer for un- supervised domain adaptation.

Towards Source-Free Machine Unlearning Do we really need to access the source data? source hypothesis transfer for un- supervised domain adaptation

Reference 23

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Observation 88f616dc-f905-4b1e-97a9-f80079019e37 · outbound

This paper cites The eu proposal for a general data protection regulation and the roots of the ‘right to be for- gotten’.

Towards Source-Free Machine Unlearning The eu proposal for a general data protection regulation and the roots of the ‘right to be for- gotten’

Reference 24

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Source-reported events for the cited work

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Observation 896b6168-3ac0-4dbb-a9ef-b6421290bba4 · outbound

This paper cites Descent-to-delete: Gradient-based methods for machine un- learning.

Towards Source-Free Machine Unlearning Descent-to-delete: Gradient-based methods for machine un- learning

Reference 25

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Source-reported events for the cited work

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Observation 1f3570c8-b98e-46df-a479-2dce72306e32 · outbound

This paper cites Fast yet effective machine unlearning.

Towards Source-Free Machine Unlearning Fast yet effective machine unlearning

Reference 26

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Source-reported events for the cited work

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Observation d1aa2ac5-593b-4a37-abde-6cc76befbc8d · outbound

This paper cites The eu general data protection regulation (gdpr).

Towards Source-Free Machine Unlearning The eu general data protection regulation (gdpr)

Reference 27

Resolution
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Source-reported events for the cited work

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Observation 9e6ca2b3-fc54-4735-8246-5ace697e18f5 · outbound

This paper cites Machine Unlearning of Features and Labels.

Towards Source-Free Machine Unlearning Machine Unlearning of Features and Labels

Reference 28

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Source-reported events for the cited work

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Observation 0c426c4f-fd67-451c-928a-7274e01883bd · outbound

This paper cites Puma: Performance unchanged model augmentation for training data removal.

Towards Source-Free Machine Unlearning Puma: Performance unchanged model augmentation for training data removal

Reference 29

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Source-reported events for the cited work

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Observation a3b9d48d-0a29-435e-909d-3274fc15fa61 · outbound

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

Towards Source-Free Machine Unlearning Delta- grad: Rapid retraining of machine learning models

Reference 30

Resolution
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Source-reported events for the cited work

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Observation 46228d44-2166-48a1-a822-0e3a99146437 · outbound

This paper cites Large Language Model Unlearning.

Towards Source-Free Machine Unlearning Large Language Model Unlearning

Reference 31

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Source-reported events for the cited work

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Observation 498b156f-39ab-4e05-b975-7a1b57d8ff54 · outbound

This paper cites Adahessian: An adap- tive second order optimizer for machine learning.

Towards Source-Free Machine Unlearning Adahessian: An adap- tive second order optimizer for machine learning

Reference 32

Resolution
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Source-reported events for the cited work

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Observation 431e4e49-2572-4838-9b86-bed4f6dd0a94 · outbound

This paper cites Learning with re- coverable forgetting.

Towards Source-Free Machine Unlearning Learning with re- coverable forgetting

Reference 33

Resolution
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Source-reported events for the cited work

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Observation ddedb19d-d4a9-44b7-9637-63c6613199d4 · outbound

This paper cites 1 2 δw⊤Mδw 2# = 1 4 E[X 2] = 1 4 2trace(M2) + trace(M)2 . (20) Simplify to obtain: E.

Towards Source-Free Machine Unlearning 1 2 δw⊤Mδw 2# = 1 4 E[X 2] = 1 4 2trace(M2) + trace(M)2 . (20) Simplify to obtain: E

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 290859bb-4c8f-4641-9dfb-744e70e1fc9c · outbound

This paper cites Performance Gap.

Towards Source-Free Machine Unlearning Performance Gap

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Pith citing papers

No inbound Pith citation observations are available.