Paper Citation Record · LEDGER

MUNBa: Machine Unlearning via Nash Bargaining

As of 21 August 2026, this Paper Citation Record lists 91 of 91 outbound references and 4 inbound Pith citation observations for arXiv:2411.15537.

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

pith.paper-citation-record.v1
2411.15537 v4

Coverage vector

measured 91 of 91 reference resolution

Typed states for the displayed outbound observations.

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measured 95 of 95 standing notices

One-hop event checks from named stored sources.

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measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:29:39.934743Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:54:37.381997Z

Reference resolution

91 of 91 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 08c5c404-032c-43b5-b582-4da52ab463b9 · outbound

This paper cites Data unlearning in diffusion models.

MUNBa: Machine Unlearning via Nash Bargaining Data unlearning in diffusion models

Reference 1

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Observation 27f1ae28-743e-4874-aab4-492c9224888c · outbound

This paper cites Nudenet: Neural nets for nudity classification, detection and selective censoring, 2019.

MUNBa: Machine Unlearning via Nash Bargaining Nudenet: Neural nets for nudity classification, detection and selective censoring, 2019

Reference 2

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Observation 77ba26e8-b00f-487c-9de9-1469abe8a28d · outbound

This paper cites Is retain set all you need in machine unlearning? restoring perfor- mance of unlearned models with out-of-distribution images.

MUNBa: Machine Unlearning via Nash Bargaining Is retain set all you need in machine unlearning? restoring perfor- mance of unlearned models with out-of-distribution images

Reference 3

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Observation 19d225c7-8200-41b6-99e5-f507bf1eda89 · outbound

This paper cites Convex optimiza- tion.

MUNBa: Machine Unlearning via Nash Bargaining Convex optimiza- tion

Reference 4

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Observation c00c1ef5-5537-4138-9ac2-7a9d618905ee · outbound

This paper cites Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts.

MUNBa: Machine Unlearning via Nash Bargaining Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts

Reference 5

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Observation df0d876a-3f45-489e-be25-01b5dea6807f · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Learning to unlearn: Instance-wise unlearning for pre-trained classifiers

Reference 6

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Observation 6481ed04-e434-4ca0-bbc9-37dd97b8ca6c · outbound

This paper cites Graph unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Graph unlearning

Reference 7

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Observation f909b350-0211-4261-9d12-f8df52768c75 · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary

Reference 8

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Observation cfd96432-b9b0-4a28-b5d7-69bdfef57db4 · outbound

This paper cites Gnndelete: A general strategy for un- learning in graph neural networks.

MUNBa: Machine Unlearning via Nash Bargaining Gnndelete: A general strategy for un- learning in graph neural networks

Reference 9

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Observation 53f85e64-b681-4cdf-9acf-ab2ad375a55f · outbound

This paper cites Zero-shot machine unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Zero-shot machine unlearning

Reference 10

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Observation 0d9b6dbd-d42c-466f-8b73-806b23705bca · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Imagenet: A large-scale hierarchical image database

Reference 11

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Observation b16a5032-c666-4e02-90f2-9e383bbfc58c · outbound

This paper cites Don't Stop Learning: Towards Continual Learning for the CLIP Model.

MUNBa: Machine Unlearning via Nash Bargaining Don't Stop Learning: Towards Continual Learning for the CLIP Model

Reference 12

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Observation 35cbb0b0-4bf7-4e1c-9373-472431bed853 · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Challenging forgets: Unveiling the worst-case forget sets in machine unlearning

Reference 13

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Observation 83c17ed2-ff9b-4ca1-a176-ae45d11acf6f · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation

Reference 14

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Observation 2ef87a5b-9b6b-4af6-bba7-5d33e0e8033d · outbound

This paper cites IMU: Influence-guided Machine Unlearning.

MUNBa: Machine Unlearning via Nash Bargaining IMU: Influence-guided Machine Unlearning

Reference 15

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Observation 9935c821-c690-42bf-9cbc-7119a41483ef · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Fast machine unlearning without retraining through selective synaptic dampening

Reference 16

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Observation 1b207ab7-9e03-4e3a-a1f3-7ca84677d247 · outbound

This paper cites Erasing concepts from diffu- sion models.

MUNBa: Machine Unlearning via Nash Bargaining Erasing concepts from diffu- sion models

Reference 17

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Observation 6031a2e2-c34c-4067-90ae-0d4e69f09c4f · outbound

This paper cites Unified Concept Editing in Diffusion Models.

MUNBa: Machine Unlearning via Nash Bargaining Unified Concept Editing in Diffusion Models

Reference 18

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Observation 3908da9f-d5d4-43a2-a030-fd716ecd0791 · outbound

This paper cites Towards Adversarial Evaluations for Inexact Machine Unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Towards Adversarial Evaluations for Inexact Machine Unlearning

Reference 19

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Observation fcb10b00-61fa-4dcc-860f-cc831296c83e · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 20

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Observation 9793bfec-a623-4b8f-9b41-b649b3d02ba6 · outbound

This paper cites Forgetting outside the box: Scrubbing deep networks of in- formation accessible from input-output observations.

MUNBa: Machine Unlearning via Nash Bargaining Forgetting outside the box: Scrubbing deep networks of in- formation accessible from input-output observations

Reference 21

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

MUNBa: Machine Unlearning via Nash Bargaining Mixed-privacy for- getting in deep networks

Reference 22

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This paper cites An introduction to the california consumer privacy act (ccpa).

MUNBa: Machine Unlearning via Nash Bargaining An introduction to the california consumer privacy act (ccpa)

Reference 23

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Observation 5a04758c-cff9-46a5-ab7f-7568a67cb2fe · outbound

This paper cites Certified data removal from machine learning models.

MUNBa: Machine Unlearning via Nash Bargaining Certified data removal from machine learning models

Reference 24

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This paper cites Federated Unlearning: How to Efficiently Erase a Client in FL?.

MUNBa: Machine Unlearning via Nash Bargaining Federated Unlearning: How to Efficiently Erase a Client in FL?

Reference 25

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This paper cites Deep residual learning for image recognition.

MUNBa: Machine Unlearning via Nash Bargaining Deep residual learning for image recognition

Reference 26

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This paper cites Continual learning for forget- ting in deep generative models.

MUNBa: Machine Unlearning via Nash Bargaining Continual learning for forget- ting in deep generative models

Reference 27

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This paper cites Selective amnesia: A contin- ual learning approach to forgetting in deep generative mod- els.

MUNBa: Machine Unlearning via Nash Bargaining Selective amnesia: A contin- ual learning approach to forgetting in deep generative mod- els

Reference 28

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This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

MUNBa: Machine Unlearning via Nash Bargaining Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 29

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This paper cites Fastai: A layered api for deep learning.

MUNBa: Machine Unlearning via Nash Bargaining Fastai: A layered api for deep learning

Reference 30

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This paper cites Model sparsification can simplify machine unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Model sparsification can simplify machine unlearning

Reference 31

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This paper cites Boosting alignment for post-unlearning text- to-image generative models.

MUNBa: Machine Unlearning via Nash Bargaining Boosting alignment for post-unlearning text- to-image generative models

Reference 32

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

MUNBa: Machine Unlearning via Nash Bargaining Understanding black- box predictions via influence functions

Reference 33

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

MUNBa: Machine Unlearning via Nash Bargaining Learning multiple layers of features from tiny images

Reference 34

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This paper cites Ablating con- cepts in text-to-image diffusion models.

MUNBa: Machine Unlearning via Nash Bargaining Ablating con- cepts in text-to-image diffusion models

Reference 35

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This paper cites Towards unbounded machine unlearn- ing.

MUNBa: Machine Unlearning via Nash Bargaining Towards unbounded machine unlearn- ing

Reference 36

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MUNBa: Machine Unlearning via Nash Bargaining Gdr-gma: Machine unlearning via direction- rectified and magnitude-adjusted gradients

Reference 37

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MUNBa: Machine Unlearning via Nash Bargaining Microsoft coco: Common objects in context

Reference 38

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This paper cites Conflict-averse gradient descent for multi-task learn- ing.

MUNBa: Machine Unlearning via Nash Bargaining Conflict-averse gradient descent for multi-task learn- ing

Reference 39

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This paper cites Famo: Fast adaptive multitask optimization.Advances in Neural In- formation Processing Systems (NeurIPS) , 36:57226–57243,.

MUNBa: Machine Unlearning via Nash Bargaining Famo: Fast adaptive multitask optimization.Advances in Neural In- formation Processing Systems (NeurIPS) , 36:57226–57243,

Reference 40

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This paper cites Federaser: Enabling efficient client-level data removal from federated learning models.

MUNBa: Machine Unlearning via Nash Bargaining Federaser: Enabling efficient client-level data removal from federated learning models

Reference 41

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This paper cites The right to be forgotten in federated learning: An efficient realization with rapid retraining.

MUNBa: Machine Unlearning via Nash Bargaining The right to be forgotten in federated learning: An efficient realization with rapid retraining

Reference 42

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This paper cites One-dimensional adapter to rule them all: Concepts diffusion models and erasing applications.

MUNBa: Machine Unlearning via Nash Bargaining One-dimensional adapter to rule them all: Concepts diffusion models and erasing applications

Reference 43

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MUNBa: Machine Unlearning via Nash Bargaining Unresolved cited work

Reference 44

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This paper cites Unrestricted black- box adversarial attack using gan with limited queries.

MUNBa: Machine Unlearning via Nash Bargaining Unrestricted black- box adversarial attack using gan with limited queries

Reference 45

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This paper cites Two-person cooperative games.

MUNBa: Machine Unlearning via Nash Bargaining Two-person cooperative games

Reference 46

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MUNBa: Machine Unlearning via Nash Bargaining Multi- task learning as a bargaining game

Reference 47

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

MUNBa: Machine Unlearning via Nash Bargaining Descent-to-delete: Gradient-based methods for machine un- learning

Reference 48

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This paper cites Reading digits in natural images with unsupervised feature learning.

MUNBa: Machine Unlearning via Nash Bargaining Reading digits in natural images with unsupervised feature learning

Reference 49

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MUNBa: Machine Unlearning via Nash Bargaining Cats and dogs

Reference 50

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This paper cites On the difficulty of training recurrent neural networks.

MUNBa: Machine Unlearning via Nash Bargaining On the difficulty of training recurrent neural networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.577906Z

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This paper cites In- context unlearning: Language models as few-shot unlearn- ers.

MUNBa: Machine Unlearning via Nash Bargaining In- context unlearning: Language models as few-shot unlearn- ers

Reference 52

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This paper cites Safe-clip: Removing nsfw concepts from vision-and-language models.

MUNBa: Machine Unlearning via Nash Bargaining Safe-clip: Removing nsfw concepts from vision-and-language models

Reference 53

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Observation 00ac7d3e-4c70-4b71-95b6-3ee5dfbac71e · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

MUNBa: Machine Unlearning via Nash Bargaining Learn- ing transferable visual models from natural language super- vision

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.530129Z

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Observation de594a96-3323-43ba-a038-885425bf865c · outbound

This paper cites Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models.

MUNBa: Machine Unlearning via Nash Bargaining Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.668652Z

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Observation 6f9ba317-41f4-48a8-a055-20e43da8ae00 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

MUNBa: Machine Unlearning via Nash Bargaining High-resolution image synthesis with latent diffusion models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.515630Z

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Observation 04fc0b36-ffc7-41a8-9d35-2ea93484df09 · outbound

This paper cites Optimization on Pareto sets: On a theory of multi-objective optimization.

MUNBa: Machine Unlearning via Nash Bargaining Optimization on Pareto sets: On a theory of multi-objective optimization

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.679628Z

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Observation 25ba5799-dedf-4a1a-8e5c-3749340d9cb1 · outbound

This paper cites Safe latent diffusion: Mitigating inappro- priate degeneration in diffusion models.

MUNBa: Machine Unlearning via Nash Bargaining Safe latent diffusion: Mitigating inappro- priate degeneration in diffusion models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.500046Z

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Observation fb3d6401-1e08-45c4-84bf-50af316e59c2 · outbound

This paper cites Remember what you want to for- get: Algorithms for machine unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Remember what you want to for- get: Algorithms for machine unlearning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.482877Z

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Observation b311ae2f-a6ab-4156-8be6-bdaf7a682427 · outbound

This paper cites Multi-task learning as multi-objective optimization.

MUNBa: Machine Unlearning via Nash Bargaining Multi-task learning as multi-objective optimization

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.466648Z

Source-reported events for the cited work

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Observation 92e570c4-817b-46b8-abff-ae45c3299144 · outbound

This paper cites Independent component alignment for multi-task learning.

MUNBa: Machine Unlearning via Nash Bargaining Independent component alignment for multi-task learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.451064Z

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Observation f105ecc4-2409-4b1a-a246-e5da1ae4a2af · outbound

This paper cites Generative unlearning for any identity.

MUNBa: Machine Unlearning via Nash Bargaining Generative unlearning for any identity

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.432322Z

Source-reported events for the cited work

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Observation abdbc3c8-7cbc-4c42-9d04-36c43ca194e3 · outbound

This paper cites Lotus: Large-scale machine unlearning with a taste of uncertainty.

MUNBa: Machine Unlearning via Nash Bargaining Lotus: Large-scale machine unlearning with a taste of uncertainty

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.417238Z

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Observation 6eaa53e6-304d-40e2-be80-901027a8c6bd · outbound

This paper cites Deep regression unlearn- ing.

MUNBa: Machine Unlearning via Nash Bargaining Deep regression unlearn- ing

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.401904Z

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Observation 29018003-868f-469e-a30f-eef50e7c4749 · outbound

This paper cites Fast yet effective machine unlearning.

MUNBa: Machine Unlearning via Nash Bargaining Fast yet effective machine unlearning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.384137Z

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Observation 21c29de8-2dfd-4dc5-bf19-a9263cfd5e36 · outbound

This paper cites Cooperative models of bargaining.

MUNBa: Machine Unlearning via Nash Bargaining Cooperative models of bargaining

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.369551Z

Source-reported events for the cited work

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Observation 0cb2fc9f-44dc-4c7b-a315-95eeadabe357 · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Unrolling sgd: Understanding factors in- fluencing machine unlearning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.730800Z

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Observation fbf1f9b8-295f-4796-a26a-3903afd58c93 · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining On the necessity of auditable algorithmic definitions for machine unlearning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.330801Z

Source-reported events for the cited work

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Observation 1ad2c5d4-0308-4835-9f57-6252cb99d7ba · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining The eu general data protection regulation (gdpr)

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.745018Z

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Observation f51d6e9c-0e5c-4fef-913c-ca25b680596f · outbound

This paper cites Federated unlearning via class-discriminative pruning.

MUNBa: Machine Unlearning via Nash Bargaining Federated unlearning via class-discriminative pruning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.307403Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9f7324f-32e6-466f-8825-d715d459b064 · outbound

This paper cites Machine Unlearning of Features and Labels.

MUNBa: Machine Unlearning via Nash Bargaining Machine Unlearning of Features and Labels

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.755167Z

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Observation edda5f27-2c17-47f8-a962-0fdb1341d19b · outbound

This paper cites Federated Unlearning with Knowledge Distillation.

MUNBa: Machine Unlearning via Nash Bargaining Federated Unlearning with Knowledge Distillation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.760470Z

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Observation a618d75c-da6d-44a7-ba0a-962bf9b78be1 · outbound

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

MUNBa: Machine Unlearning via Nash Bargaining Puma: Performance unchanged model augmentation for training data removal

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.293256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b5cf256d-333e-4363-b2a9-4636fbc72722 · outbound

This paper cites Scissorhands: Scrub data influence via connection sensitivity in networks.

MUNBa: Machine Unlearning via Nash Bargaining Scissorhands: Scrub data influence via connection sensitivity in networks

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.279488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bf59146e-7901-4c4b-b2de-e0889509b9b7 · outbound

This paper cites Erasing undesirable influence in diffusion models.

MUNBa: Machine Unlearning via Nash Bargaining Erasing undesirable influence in diffusion models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.263918Z

Source-reported events for the cited work

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Observation ce69167f-ccf0-4afd-9869-25cbe5810d61 · outbound

This paper cites Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set.

MUNBa: Machine Unlearning via Nash Bargaining Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.249227Z

Source-reported events for the cited work

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Observation 33e7df21-66b7-4d8c-ad72-02993d60d904 · outbound

This paper cites Gradient surgery for multi-task learning.

MUNBa: Machine Unlearning via Nash Bargaining Gradient surgery for multi-task learning

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.234290Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation db957df5-483b-4158-88b9-0275361e65fe · outbound

This paper cites Fairness-Aware Meta-Learning via Nash Bargaining.

MUNBa: Machine Unlearning via Nash Bargaining Fairness-Aware Meta-Learning via Nash Bargaining

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:16:47.944733Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f3728e7-912d-405d-995f-21ab7698020e · outbound

This paper cites Investigating the catastrophic for- getting in multimodal large language models.

MUNBa: Machine Unlearning via Nash Bargaining Investigating the catastrophic for- getting in multimodal large language models

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.219672Z

Source-reported events for the cited work

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Observation 7a7abe5f-4fed-4b9a-b78d-c55051f293f2 · outbound

This paper cites Ver- ification of machine unlearning is fragile.

MUNBa: Machine Unlearning via Nash Bargaining Ver- ification of machine unlearning is fragile

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.204097Z

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Observation 22adf498-73da-44d4-881c-beb080f593ed · outbound

This paper cites Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models.

MUNBa: Machine Unlearning via Nash Bargaining Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.804987Z

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Observation e045d834-777d-4b32-ac6e-69cc499f6031 · outbound

This paper cites Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models.

MUNBa: Machine Unlearning via Nash Bargaining Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.810244Z

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Observation bcc1d248-cf98-42ea-b995-a26a11a6e68e · outbound

This paper cites UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models.

MUNBa: Machine Unlearning via Nash Bargaining UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.815008Z

Source-reported events for the cited work

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Observation 9f54ef70-a608-45fc-a2f8-376abc43d798 · outbound

This paper cites To gen- erate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images.

MUNBa: Machine Unlearning via Nash Bargaining To gen- erate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.186464Z

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Observation ae3e9028-3e26-4803-b286-55b1311c4f67 · outbound

This paper cites Exploring Federated Unlearning: Review, Comparison, and Insights.

MUNBa: Machine Unlearning via Nash Bargaining Exploring Federated Unlearning: Review, Comparison, and Insights

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-12T14:16:47.824189Z

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Observation 9837b2bf-14ff-43f1-91f5-5f6848941fcb · outbound

This paper cites an unresolved cited work.

MUNBa: Machine Unlearning via Nash Bargaining Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:16:48.169963Z

Source-reported events for the cited work

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Observation aee5df2f-2a81-41a1-b5ba-06e78592f265 · outbound

This paper cites (30) Denote α2 r as z, we have a quadratic equation in terms of z: (g2 1g3 − g1g2.

MUNBa: Machine Unlearning via Nash Bargaining (30) Denote α2 r as z, we have a quadratic equation in terms of z: (g2 1g3 − g1g2

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.153983Z

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Observation 2d0abd01-7a99-4543-b43d-213cbaa902ae · outbound

This paper cites (31) With the quadratic formula, we have: z = 2g1g3 ± p 4g2 1g2 3 − 4(g2 1g3 − g1g2 2)g3 2(g2 1g3 − g1g2 2) = g1g3 ± g2 √g1g3 g2 1g3 − g1g2 2.

MUNBa: Machine Unlearning via Nash Bargaining (31) With the quadratic formula, we have: z = 2g1g3 ± p 4g2 1g2 3 − 4(g2 1g3 − g1g2 2)g3 2(g2 1g3 − g1g2 2) = g1g3 ± g2 √g1g3 g2 1g3 − g1g2 2

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.136300Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c652f9ed-bae9-4342-9850-8cebc2c7a817 · outbound

This paper cites We mainly follow the settings in SalUn [14] for image classification.

MUNBa: Machine Unlearning via Nash Bargaining We mainly follow the settings in SalUn [14] for image classification

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.121042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 971a903e-4fa9-44d6-9dd3-053d8e4c633d · outbound

This paper cites Computational complexity MUNBa won’t induce extra parameters.

MUNBa: Machine Unlearning via Nash Bargaining Computational complexity MUNBa won’t induce extra parameters

Reference 91

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T14:16:48.104393Z

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Observation 7aac533d-6e5f-46fa-ae3d-313ec039530f · outbound

This paper cites 1, 5, 6, 7, 9, 10, 12.

MUNBa: Machine Unlearning via Nash Bargaining 1, 5, 6, 7, 9, 10, 12

Reference 319

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:16:48.346626Z

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Pith citing papers

Observation 47dc23fe-5225-4f7e-ab00-0600e802bce1 · inbound

Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts cites this paper.

Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts MUNBa: Machine Unlearning via Nash Bargaining

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-16T12:29:39.934743Z

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Observation d14988e1-debf-4bc2-ac95-791dde5ea5c6 · inbound

Erasing Concepts, Steering Generations: A Comprehensive Survey of Concept Suppression cites this paper.

Erasing Concepts, Steering Generations: A Comprehensive Survey of Concept Suppression MUNBa: Machine Unlearning via Nash Bargaining

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-07T14:19:56.313019Z

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Observation 009b56d8-be34-41a6-8aa5-0d06a6912bc5 · inbound

Rethinking Machine Unlearning in Image Generation Models cites this paper.

Rethinking Machine Unlearning in Image Generation Models MUNBa: Machine Unlearning via Nash Bargaining

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T11:22:51.737043Z

Source-reported events for the cited work

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Observation 4165f88a-80c6-482a-a8b3-eea9a00c2ed6 · inbound

Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI cites this paper.

Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI MUNBa: Machine Unlearning via Nash Bargaining

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:54:37.387393Z

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