Paper Citation Record · LEDGER

NOVO: Unlearning-Compliant Vision Transformers

As of 7 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2507.03281.

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

pith.paper-citation-record.v1
2507.03281 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:23:44.006979Z

measured 51 of 51 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:25:57.025905Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:28:12.051792Z

Reference resolution

50 of 50 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 864c4184-983d-49d9-9fbd-460491d79de1 · outbound

This paper cites https://oag.ca.gov/privacy/ccpa, 2018.

NOVO: Unlearning-Compliant Vision Transformers https://oag.ca.gov/privacy/ccpa, 2018

Reference 1

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Observation aa0bbdd1-13d0-4474-8fac-552065e031ed · outbound

This paper cites https://gdpr- info.eu/, 2018.

NOVO: Unlearning-Compliant Vision Transformers https://gdpr- info.eu/, 2018

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:50.555764Z

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Observation 912987cf-28fb-4510-b22c-0bc9328506ef · outbound

This paper cites GPT-4 Technical Report.

NOVO: Unlearning-Compliant Vision Transformers GPT-4 Technical Report

Reference 3

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Observation b0581756-c421-4dca-8cc5-549a7d949ca1 · outbound

This paper cites Machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Machine unlearning

Reference 4

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Observation a83458a2-5430-40cc-8a7e-ec84eefc4c1d · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Towards making systems for- get with machine unlearning

Reference 5

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Observation 5b3625be-6aa3-4de8-a84f-918ac9038ca0 · outbound

This paper cites Learning to unlearn: Instance-wise unlearning for pre-trained classifiers, 2024.

NOVO: Unlearning-Compliant Vision Transformers Learning to unlearn: Instance-wise unlearning for pre-trained classifiers, 2024

Reference 6

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Observation ffdeff97-218e-4537-9f44-f2747a5d5a47 · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary

Reference 7

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Observation efd07fb4-39be-47d4-860f-f5f2c8743278 · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:50.082899Z

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Observation ace19093-0acb-4a29-a91b-8d44d294ac0d · outbound

This paper cites Zero-shot machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Zero-shot machine unlearning

Reference 9

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Observation 4037c42b-8db8-4687-8443-68c66ba2ae7f · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Imagenet: A large-scale hierarchical image database

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:49.705426Z

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Observation 61991168-33d9-4985-8b76-953c67e5baa9 · outbound

This paper cites InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model.

NOVO: Unlearning-Compliant Vision Transformers InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model

Reference 11

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Observation d67611dc-1e1b-464f-9b7b-68bb9ed388cc · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

NOVO: Unlearning-Compliant Vision Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Observation d698b7c6-318f-4f06-88e6-c9d0c84c8974 · outbound

This paper cites Challenging forgets: Unveiling the worst-case forget sets in machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Challenging forgets: Unveiling the worst-case forget sets in machine unlearning

Reference 13

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Observation 470c5f23-7054-4c82-b24c-d48925aa137f · outbound

This paper cites Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation.

NOVO: Unlearning-Compliant Vision Transformers Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation

Reference 14

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Observation 51ce0099-a119-432b-a2f9-bf81291eba10 · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Fast machine unlearning without retraining through selective synaptic dampening

Reference 15

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Observation efbbc4fe-1503-48f6-a121-6e636b65a57d · outbound

This paper cites How to train vision transformer on small-scale datasets? In 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022.

NOVO: Unlearning-Compliant Vision Transformers How to train vision transformer on small-scale datasets? In 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022

Reference 16

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Observation 2a88a2d4-1697-4bee-8ece-1a23ced91eba · outbound

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

NOVO: Unlearning-Compliant Vision Transformers Mixed-privacy for- getting in deep networks

Reference 17

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Observation 0ad04a51-7bb0-424d-91ee-47515c264e3d · outbound

This paper cites Amne- siac machine learning.

NOVO: Unlearning-Compliant Vision Transformers Amne- siac machine learning

Reference 18

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Observation c2fd63b3-02f7-4702-8a0a-4ec1e9a3350e · outbound

This paper cites Certified data removal from machine learning models.

NOVO: Unlearning-Compliant Vision Transformers Certified data removal from machine learning models

Reference 19

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Observation dcdd2191-07ed-4aa6-bb47-16adf087236a · outbound

This paper cites Towards Independence Criterion in Machine Unlearning of Features and Labels.

NOVO: Unlearning-Compliant Vision Transformers Towards Independence Criterion in Machine Unlearning of Features and Labels

Reference 20

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Observation 890558d5-5a3d-49fe-a6c2-1973aeb9aaa8 · outbound

This paper cites Model sparsity can simplify machine unlearning, 2024.

NOVO: Unlearning-Compliant Vision Transformers Model sparsity can simplify machine unlearning, 2024

Reference 21

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Observation 3e876b70-dd7a-4c05-9db5-f2be9544d526 · outbound

This paper cites Vi- sual prompt tuning.

NOVO: Unlearning-Compliant Vision Transformers Vi- sual prompt tuning

Reference 22

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Observation a58156cb-893f-4593-b6ee-705fbde2b9a9 · outbound

This paper cites Layer attack unlearning: Fast and accurate machine unlearning via layer level attack and knowledge distillation.

NOVO: Unlearning-Compliant Vision Transformers Layer attack unlearning: Fast and accurate machine unlearning via layer level attack and knowledge distillation

Reference 23

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Observation 7f174511-c596-42de-a063-8b9099881a95 · outbound

This paper cites Overcoming catastrophic forgetting in neu- ral networks.

NOVO: Unlearning-Compliant Vision Transformers Overcoming catastrophic forgetting in neu- ral networks

Reference 24

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

NOVO: Unlearning-Compliant Vision Transformers Learning multiple layers of features from tiny images

Reference 25

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Observation 77b4a219-24cb-41dc-b005-65a5fbc81bb0 · outbound

This paper cites Towards unbounded machine unlearn- ing.

NOVO: Unlearning-Compliant Vision Transformers Towards unbounded machine unlearn- ing

Reference 26

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NOVO: Unlearning-Compliant Vision Transformers Unresolved cited work

Reference 27

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This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

NOVO: Unlearning-Compliant Vision Transformers BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 28

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

NOVO: Unlearning-Compliant Vision Transformers Erm-ktp: Knowledge-level machine un- learning via knowledge transfer

Reference 29

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Observation 422c7c3b-b185-490e-91c4-9197be26a091 · outbound

This paper cites Continual learning and private unlearning.

NOVO: Unlearning-Compliant Vision Transformers Continual learning and private unlearning

Reference 30

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Observation 63af285e-8593-45be-885e-bd94e32430a5 · outbound

This paper cites Visual instruction tuning.

NOVO: Unlearning-Compliant Vision Transformers Visual instruction tuning

Reference 31

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This paper cites Model spar- sity can simplify machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Model spar- sity can simplify machine unlearning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:46.932327Z

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Observation 855b65bf-5eeb-4e46-884b-6e9f3d9644b6 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

NOVO: Unlearning-Compliant Vision Transformers Swin transformer: Hierarchical vision transformer using shifted windows

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:46.644942Z

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Observation 282f30e1-0d1d-4df3-91b3-0b480b807d82 · outbound

This paper cites Fair machine unlearning: Data removal while mitigating disparities.

NOVO: Unlearning-Compliant Vision Transformers Fair machine unlearning: Data removal while mitigating disparities

Reference 34

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Observation e06a6f3a-af4d-4261-a36a-7eeb1a26d95b · outbound

This paper cites Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective.

NOVO: Unlearning-Compliant Vision Transformers Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective

Reference 35

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Observation 492abe7c-26fa-4d71-a904-50924b33f9e0 · outbound

This paper cites amnesia–towards machine learning mod- els that can forget user data very fast.

NOVO: Unlearning-Compliant Vision Transformers amnesia–towards machine learning mod- els that can forget user data very fast

Reference 36

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Observation 7b4cd4e5-a779-4f73-b48d-0abafb182300 · outbound

This paper cites Parameter-tuning-free data entry error unlearning with adap- tive selective synaptic dampening, 2024.

NOVO: Unlearning-Compliant Vision Transformers Parameter-tuning-free data entry error unlearning with adap- tive selective synaptic dampening, 2024

Reference 37

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Observation e87a3758-022b-438a-9144-7fdc30f79285 · outbound

This paper cites Federated Unlearning: a Perspective of Stability and Fairness.

NOVO: Unlearning-Compliant Vision Transformers Federated Unlearning: a Perspective of Stability and Fairness

Reference 38

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This paper cites Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models.

NOVO: Unlearning-Compliant Vision Transformers Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models

Reference 39

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This paper cites Deep Regression Unlearning.

NOVO: Unlearning-Compliant Vision Transformers Deep Regression Unlearning

Reference 40

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NOVO: Unlearning-Compliant Vision Transformers Deep regression unlearn- ing

Reference 41

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Observation 4dd51926-cf42-439b-a06e-a1bd405d4d29 · outbound

This paper cites Fast yet effective machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Fast yet effective machine unlearning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:45.464804Z

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Observation 39b5d5cc-9df1-4073-b61e-52b3352e52f3 · outbound

This paper cites Unrolling sgd: Understanding factors in- fluencing machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Unrolling sgd: Understanding factors in- fluencing machine unlearning

Reference 43

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NOVO: Unlearning-Compliant Vision Transformers Going deeper with Image Transformers

Reference 44

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NOVO: Unlearning-Compliant Vision Transformers Going deeper with im- age transformers

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:45.226670Z

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Observation 072590ea-20f8-4837-a647-718c708680ab · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

NOVO: Unlearning-Compliant Vision Transformers Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 46

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NOVO: Unlearning-Compliant Vision Transformers Visualizing data using t-sne

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:44.987667Z

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Observation dd3dfaee-6258-4133-8d56-977e3bc7a981 · outbound

This paper cites A Comparative Study of Open-Source Large Language Models, GPT-4 and Claude 2: Multiple-Choice Test Taking in Nephrology.

NOVO: Unlearning-Compliant Vision Transformers A Comparative Study of Open-Source Large Language Models, GPT-4 and Claude 2: Multiple-Choice Test Taking in Nephrology

Reference 48

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

NOVO: Unlearning-Compliant Vision Transformers Delta- grad: Rapid retraining of machine learning models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:44.781619Z

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Observation 4453446f-4e24-451d-8dc8-061174c36432 · outbound

This paper cites Arcane: An efficient architecture for exact machine unlearning.

NOVO: Unlearning-Compliant Vision Transformers Arcane: An efficient architecture for exact machine unlearning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:23:44.554896Z

Source-reported events for the cited work

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Pith citing papers

Observation 7b10be84-10bc-45fd-bf37-29f7a8f74bd5 · inbound

Interference-Aware Multi-Task Unlearning cites this paper.

Interference-Aware Multi-Task Unlearning NOVO: Unlearning-Compliant Vision Transformers

Reference 47

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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.