Paper Citation Record · LEDGER

Siamese Machine Unlearning with Knowledge Vaporization and Concentration

As of 23 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2412.01207.

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pith.paper-citation-record.v1
2412.01207 v1

Coverage vector

measured 40 of 40 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 5a1c2690-253d-4c14-b9c4-d3311aaf9c41 · outbound

This paper cites Fully-convolutional siamese networks for object tracking.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Fully-convolutional siamese networks for object tracking

Reference 1

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Observation 6c32812c-cda1-4f33-9d52-f8c88898b33e · outbound

This paper cites Machine unlearning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Machine unlearning

Reference 2

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Observation baf2075e-79a1-4f39-bcc8-88555b3a427b · outbound

This paper cites Signature verification using a” siamese” time delay neural network.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Signature verification using a” siamese” time delay neural network

Reference 3

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Observation 58abaecc-8d55-4ff2-b86b-d1f0d9b4b1b8 · outbound

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Towards making systems for- get with machine unlearning

Reference 4

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Observation b4fd7b25-debd-4f18-a216-180c1ec3eeb8 · outbound

This paper cites Graph unlearning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Graph unlearning

Reference 5

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Observation f018fa2c-135f-4f9b-8e39-feadfa07822b · outbound

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary

Reference 6

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Observation 0bac54d9-5214-44f9-a145-33151b6c317e · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration A simple framework for contrastive learning of visual representations

Reference 7

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Observation eedc052f-6b9a-493e-8f2b-6dcde987ce49 · outbound

This paper cites Exploring simple siamese rep- resentation learning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Exploring simple siamese rep- resentation learning

Reference 8

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher

Reference 9

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Observation fa0e3478-f519-4d0c-9ba2-fdbd5c526393 · outbound

This paper cites Zero-shot machine unlearning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Zero-shot machine unlearning

Reference 10

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Observation 8efb56a0-3693-4f7a-94ca-247d492d451e · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Improved Regularization of Convolutional Neural Networks with Cutout

Reference 11

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Observation 59e27e02-1f89-4d81-bed7-995104f75bcd · outbound

This paper cites Fast machine unlearning without retraining through selective synaptic dampening.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Fast machine unlearning without retraining through selective synaptic dampening

Reference 12

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Observation f7184d2f-8339-417b-a48b-6cd72c72c781 · outbound

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Making ai forget you: Data deletion in ma- chine learning

Reference 13

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 14

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This paper cites Amne- siac machine learning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Amne- siac machine learning

Reference 15

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This paper cites Deep residual learning for image recognition.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Deep residual learning for image recognition

Reference 16

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This paper cites Siamese neural networks for one-shot image recognition.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Siamese neural networks for one-shot image recognition

Reference 17

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Observation 4e7248f3-b133-42fa-b958-06ec9c27adf1 · outbound

This paper cites Understanding black-box predictions via influence functions.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Understanding black-box predictions via influence functions

Reference 18

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Observation ee1efdaa-dbc2-415d-8755-5866b7fe2994 · outbound

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Learning multiple layers of features from tiny images

Reference 19

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This paper cites Towards unbounded machine unlearn- ing.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Towards unbounded machine unlearn- ing

Reference 20

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This paper cites Erm-ktp: Knowledge-level machine un- learning via knowledge transfer.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Erm-ktp: Knowledge-level machine un- learning via knowledge transfer

Reference 21

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This paper cites New insights and perspectives on the natural gradient method.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration New insights and perspectives on the natural gradient method

Reference 22

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This paper cites A Survey of Machine Unlearning.

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

Reference 23

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This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 24

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This paper cites Systematic evaluation of pri- vacy risks of machine learning models.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Systematic evaluation of pri- vacy risks of machine learning models

Reference 25

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This paper cites Deepface: Closing the gap to human-level perfor- mance in face verification.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Deepface: Closing the gap to human-level perfor- mance in face verification

Reference 26

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This paper cites Tarun, Vikram S.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Tarun, Vikram S

Reference 27

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This paper cites On the necessity of auditable algorithmic definitions for machine unlearning.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration On the necessity of auditable algorithmic definitions for machine unlearning

Reference 28

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This paper cites What makes for good views for contrastive learning? Advances in neural informa- tion processing systems, 33:6827–6839, 2020.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration What makes for good views for contrastive learning? Advances in neural informa- tion processing systems, 33:6827–6839, 2020

Reference 29

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This paper cites Machine unlearning via algorithmic stability.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Machine unlearning via algorithmic stability

Reference 30

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This paper cites Demys- tifying the draft eu artificial intelligence act—analysing the good, the bad, and the unclear elements of the proposed ap- proach.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Demys- tifying the draft eu artificial intelligence act—analysing the good, the bad, and the unclear elements of the proposed ap- proach

Reference 31

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

Siamese Machine Unlearning with Knowledge Vaporization and Concentration The eu general data protection regulation (gdpr)

Reference 32

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This paper cites Machine Unlearning of Features and Labels.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Machine Unlearning of Features and Labels

Reference 33

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This paper cites Randomized response: A survey tech- nique for eliminating evasive answer bias.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Randomized response: A survey tech- nique for eliminating evasive answer bias

Reference 34

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Observation fbf611ca-69d3-4575-b730-76c48c8f1c61 · outbound

This paper cites Using the CIFAR-10 dataset, we train the VGG16-BN solely on the remaining data across three unlearning scenarios:.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Using the CIFAR-10 dataset, we train the VGG16-BN solely on the remaining data across three unlearning scenarios:

Reference 35

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Siamese Machine Unlearning with Knowledge Vaporization and Concentration Unresolved cited work

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Siamese Machine Unlearning with Knowledge Vaporization and Concentration Unresolved cited work

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This paper cites Moreover, we utilize data augmentation and observe the response of the retrained models toward the augmentations of data points.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration Moreover, we utilize data augmentation and observe the response of the retrained models toward the augmentations of data points

Reference 38

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Siamese Machine Unlearning with Knowledge Vaporization and Concentration Predictor design

Reference 39

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This paper cites 99.86 0.00 93.58 0.00 0.03.

Siamese Machine Unlearning with Knowledge Vaporization and Concentration 99.86 0.00 93.58 0.00 0.03

Reference 40

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Pith citing papers

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