Learning to Forget using Hypernetworks | Paper Citation Record

Observation 0ba25573-f0b8-4384-8e33-fe5cda691a91 · outbound

This paper cites Machine unlearning: Linear filtration for logit-based classifiers.

Learning to Forget using Hypernetworks Machine unlearning: Linear filtration for logit-based classifiers

Reference 1

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Observation d7302240-47ab-4927-aab7-46439ab0aebe · outbound

This paper cites Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot.

Learning to Forget using Hypernetworks Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot

Reference 2

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Observation affbbfcf-36f4-4bbf-a788-ea81aa98ab64 · outbound

This paper cites Machine unlearning for random forests.

Learning to Forget using Hypernetworks Machine unlearning for random forests

Reference 3

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Observation 3794d2f2-d072-479d-b81b-719b2545aa36 · outbound

This paper cites Towards making systems forget with machine unlearning.

Learning to Forget using Hypernetworks Towards making systems forget with machine unlearning

Reference 4

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Observation da8c62da-e67d-45c3-bcb3-24d54d5ed708 · outbound

This paper cites Poisoning web-scale training datasets is practical.

Learning to Forget using Hypernetworks Poisoning web-scale training datasets is practical

Reference 5

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Observation f1e6c70e-c24d-4fda-8b13-48ef682e0d5b · outbound

This paper cites A Brief Review of Hypernetworks in Deep Learning.

Learning to Forget using Hypernetworks A Brief Review of Hypernetworks in Deep Learning

Reference 6

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Observation df7421a7-a3a3-4bf1-b719-f7b48dc5d85d · outbound

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

Learning to Forget using Hypernetworks Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher

Reference 7

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Observation 243f5f2a-0d01-4641-83e3-c1ba5e4572ea · outbound

This paper cites Zero-shot machine unlearning.

Learning to Forget using Hypernetworks Zero-shot machine unlearning

Reference 8

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Observation c0c7efc4-9005-4d4f-8927-61870d2220f1 · outbound

This paper cites Davis and Yi Zhong.

Learning to Forget using Hypernetworks Davis and Yi Zhong

Reference 9

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Observation fbded094-13ca-4646-827d-6dd4c779b258 · outbound

This paper cites Hyperdiffusion: Generating implicit neural fields with weight-space diffusion.

Learning to Forget using Hypernetworks Hyperdiffusion: Generating implicit neural fields with weight-space diffusion

Reference 10

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Observation f9442a94-0208-4734-8590-07b813898f51 · outbound

This paper cites an unresolved cited work.

Learning to Forget using Hypernetworks Unresolved cited work

Reference 11

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Observation 08fc77b4-3d4f-4e5e-8488-dd832323d835 · outbound

This paper cites An information theoretic approach to machine unlearning, 2024.

Learning to Forget using Hypernetworks An information theoretic approach to machine unlearning, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.812918Z

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Observation f4b112fc-c28c-40a7-8b88-a68e87a5fe6a · outbound

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

Learning to Forget using Hypernetworks Fast machine unlearning without retraining through selective synaptic dampening

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.803772Z

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Observation 97493dc7-4469-4375-8fa2-80f27c139a32 · outbound

This paper cites Making ai forget you: Data deletion in machine learning.

Learning to Forget using Hypernetworks Making ai forget you: Data deletion in machine learning

Reference 14

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Observation 97854ec9-e650-42aa-91f1-b5391c2ea0e2 · outbound

This paper cites Towards Adversarial Evaluations for Inexact Machine Unlearning.

Learning to Forget using Hypernetworks Towards Adversarial Evaluations for Inexact Machine Unlearning

Reference 15

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This paper cites Corrective machine unlearning.

Learning to Forget using Hypernetworks Corrective machine unlearning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.791903Z

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Observation 76f92bff-d149-4ac9-b0f1-2c94cc043733 · outbound

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

Learning to Forget using Hypernetworks Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 17

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Observation 54c578bc-6cc3-4911-a1cf-c64f43884a96 · outbound

This paper cites Amnesiac machine learning.

Learning to Forget using Hypernetworks Amnesiac machine learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.779693Z

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Observation 140d6b7c-16ad-4b4b-962e-01f1638d35d1 · outbound

This paper cites Certified Data Removal from Machine Learning Models.

Learning to Forget using Hypernetworks Certified Data Removal from Machine Learning Models

Reference 19

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Observation 0dcdb12d-5215-4a07-90b0-944c2ca506f9 · outbound

This paper cites HyperNetworks.

Learning to Forget using Hypernetworks HyperNetworks

Reference 20

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Observation 8e3fead3-a37e-4c29-83a0-8c547b31a685 · outbound

This paper cites DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks.

Learning to Forget using Hypernetworks DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks

Reference 21

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Observation 77ca5f94-fc44-48d5-89d8-8b8cdadd292d · outbound

This paper cites Denoising diffusion probabilistic models.

Learning to Forget using Hypernetworks Denoising diffusion probabilistic models

Reference 22

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Observation d61aa829-140c-4d75-80c4-41e6bfbbf621 · outbound

This paper cites Predictive Uncertainty Quantification with Compound Density Networks.

Learning to Forget using Hypernetworks Predictive Uncertainty Quantification with Compound Density Networks

Reference 23

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Observation 7b95ea44-8b8c-4685-adec-6b11901e91e2 · outbound

This paper cites Towards unbounded machine unlearning.

Learning to Forget using Hypernetworks Towards unbounded machine unlearning

Reference 24

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Observation b8bb3af0-0783-43ec-a855-c049040e0b79 · outbound

This paper cites Dhp: Differentiable meta pruning via hypernetworks.

Learning to Forget using Hypernetworks Dhp: Differentiable meta pruning via hypernetworks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.761077Z

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Observation bb5d2b00-5802-433b-bb65-51a24acc8b57 · outbound

This paper cites The heterogeneity hypothesis: Finding layer-wise differentiated network architectures.

Learning to Forget using Hypernetworks The heterogeneity hypothesis: Finding layer-wise differentiated network architectures

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.753512Z

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Observation acefb9ba-c267-4e58-84b4-2f7f153fac8c · outbound

This paper cites Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization.

Learning to Forget using Hypernetworks Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization

Reference 27

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Observation 9058515f-f44d-4285-950e-24fae4c36e92 · outbound

This paper cites Rethinking Machine Unlearning for Large Language Models.

Learning to Forget using Hypernetworks Rethinking Machine Unlearning for Large Language Models

Reference 28

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Observation 6704f7f7-f123-4279-a20b-744b988b8fec · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning to Forget using Hypernetworks Decoupled Weight Decay Regularization

Reference 29

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Observation 34805db6-bcf4-4a48-86a6-cad725a6376c · outbound

This paper cites Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks.

Learning to Forget using Hypernetworks Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T05:05:52.322077Z

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Observation 235250c3-fce3-480b-b112-bbcf221e1a28 · outbound

This paper cites Hard to forget: Poisoning attacks on certified machine unlearning.

Learning to Forget using Hypernetworks Hard to forget: Poisoning attacks on certified machine unlearning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.745812Z

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Observation 7df33fc6-2a13-4214-b70a-a496d2852a3b · outbound

This paper cites Zero-shot knowledge transfer via adversarial belief matching.Advances in Neural Information Processing Systems, 32, 2019.

Learning to Forget using Hypernetworks Zero-shot knowledge transfer via adversarial belief matching.Advances in Neural Information Processing Systems, 32, 2019

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.738531Z

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Observation f55412b2-0211-4f4c-b3ce-f783dba7f9f5 · outbound

This paper cites Forgetting as a consequence of retrieval: a meta-analytic review of retrieval-induced forgetting.

Learning to Forget using Hypernetworks Forgetting as a consequence of retrieval: a meta-analytic review of retrieval-induced forgetting

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.731060Z

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Observation 30c525de-ea6a-45e9-94f3-58f61b8e551c · outbound

This paper cites Feder Cooper, Daphne Ippolito, Christopher A.

Learning to Forget using Hypernetworks Feder Cooper, Daphne Ippolito, Christopher A

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.723534Z

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Observation c3cbec9c-2c19-4a74-af5f-eb9dae11dc97 · outbound

This paper cites A Survey of Machine Unlearning.

Learning to Forget using Hypernetworks A Survey of Machine Unlearning

Reference 35

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Observation 6754dc47-8624-414a-8f34-e04ee36c6e3c · outbound

This paper cites CVAE-H: Conditionalizing Variational Autoencoders via Hypernetworks and Trajectory Forecasting for Autonomous Driving.

Learning to Forget using Hypernetworks CVAE-H: Conditionalizing Variational Autoencoders via Hypernetworks and Trajectory Forecasting for Autonomous Driving

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:05:52.463573Z

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Observation b3b925f3-67a5-45dc-ba73-70bfb6807cf2 · outbound

This paper cites Learning to learn with generative models of neural network checkpoints.

Learning to Forget using Hypernetworks Learning to learn with generative models of neural network checkpoints

Reference 37

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Observation 59d396d6-9827-4370-bc9e-a787a964b022 · outbound

This paper cites Scalable diffusion models with transformers.

Learning to Forget using Hypernetworks Scalable diffusion models with transformers

Reference 38

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Observation c80ac897-c42b-4380-9715-a71ce711e44b · outbound

This paper cites Adversarial attacks and defenses in deep learning.

Learning to Forget using Hypernetworks Adversarial attacks and defenses in deep learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.705796Z

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Observation 01f257af-8fec-451b-a5f7-defbb290b05a · outbound

This paper cites On linear identifiability of learned representations.

Learning to Forget using Hypernetworks On linear identifiability of learned representations

Reference 40

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Observation 98f0967e-054a-4d5d-9dea-641203fe6c45 · outbound

This paper cites Potion: Towards Poison Unlearning.

Learning to Forget using Hypernetworks Potion: Towards Poison Unlearning

Reference 41

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Observation 6289ea4e-e265-4bbe-9c0f-53aae0761694 · outbound

This paper cites Self-supervised representation learning on neural network weights for model characteristic prediction.

Learning to Forget using Hypernetworks Self-supervised representation learning on neural network weights for model characteristic prediction

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.694625Z

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Observation b6493baa-f43e-4fb4-88b0-f0faa8022d03 · outbound

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

Learning to Forget using Hypernetworks Remember what you want to forget: Algorithms for machine unlearning

Reference 43

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Observation 3f7964f9-3791-43a1-8bc8-da59d9a71292 · outbound

This paper cites The seven sins of Personal-Data processing systems under GDPR.

Learning to Forget using Hypernetworks The seven sins of Personal-Data processing systems under GDPR

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.683311Z

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Observation 794d5587-5769-4c55-80a1-a300fbc586a4 · outbound

This paper cites forgetting.

Learning to Forget using Hypernetworks forgetting

Reference 45

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Observation 82ee88aa-83db-493a-9153-88b61a19e6ce · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Learning to Forget using Hypernetworks Deep unsupervised learning using nonequilibrium thermodynamics

Reference 46

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Observation 9b8bcd46-3540-4c43-88ef-afaa05a174a3 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Learning to Forget using Hypernetworks Score-Based Generative Modeling through Stochastic Differential Equations

Reference 47

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Observation 110247a9-03d2-4901-a949-4a4d5216bc85 · outbound

This paper cites Fast yet effective machine unlearning.

Learning to Forget using Hypernetworks Fast yet effective machine unlearning

Reference 48

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Observation a7c88c96-9aa4-427d-b725-e57acdc9c195 · outbound

This paper cites Unrolling sgd: Understanding factors influencing machine unlearning.

Learning to Forget using Hypernetworks Unrolling sgd: Understanding factors influencing machine unlearning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.660942Z

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Observation 8784f8a1-284f-4651-bad2-4ba9ca7e8e0f · outbound

This paper cites Unrolling sgd: Understanding factors influencing machine unlearning.

Learning to Forget using Hypernetworks Unrolling sgd: Understanding factors influencing machine unlearning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.652657Z

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Observation 04d23d43-ec97-49e2-846e-d051b58ef762 · outbound

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

Learning to Forget using Hypernetworks The eu general data protection regulation (gdpr)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.644321Z

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Observation de13b6ae-2a27-4a8f-a854-d47803ddaf31 · outbound

This paper cites Example-based Hypernetworks for Out-of-Distribution Generalization.

Learning to Forget using Hypernetworks Example-based Hypernetworks for Out-of-Distribution Generalization

Reference 52

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Observation bf14c11f-e337-4d93-a736-c9792a9c0588 · outbound

This paper cites Continual learning with hypernetworks.

Learning to Forget using Hypernetworks Continual learning with hypernetworks

Reference 53

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Observation c403eca7-df90-452c-80f3-4ee39dda4a5f · outbound

This paper cites Neural network diffusion.

Learning to Forget using Hypernetworks Neural network diffusion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.636282Z

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Observation c963e412-6467-4dec-b185-1254da57fe09 · outbound

This paper cites Machine Unlearning: A Comprehensive Survey.

Learning to Forget using Hypernetworks Machine Unlearning: A Comprehensive Survey

Reference 55

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Observation 4123c0a6-1b28-49d8-ab87-d9c057ae0677 · outbound

This paper cites Few-Shot Unlearning by Model Inversion.

Learning to Forget using Hypernetworks Few-Shot Unlearning by Model Inversion

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T05:05:52.387900Z

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Observation a3b94879-b409-470f-a121-c215c126746f · outbound

This paper cites Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions.

Learning to Forget using Hypernetworks Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T05:05:52.390506Z

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Observation 7cff7d52-3896-4445-9818-d285e4dc93f5 · outbound

This paper cites A review on machine unlearning.

Learning to Forget using Hypernetworks A review on machine unlearning

Reference 58

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Observation 5efafdaa-b802-4a98-9be1-4eb8ad0e7ffc · outbound

This paper cites A.4 Additional details on evaluation metrics Each model must be evaluated on two key aspects.

Learning to Forget using Hypernetworks A.4 Additional details on evaluation metrics Each model must be evaluated on two key aspects

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:05:52.618889Z

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