Paper Citation Record · LEDGER

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.08464.

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

pith.paper-citation-record.v1
2506.08464 v2

Coverage vector

measured 44 of 44 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-07T05:17:10.648494Z

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Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation 1d46f501-35ee-49cf-8e55-3bb8092121ca · outbound

This paper cites Natural gradient works efficiently in learning.Neural Computation, 1998.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Natural gradient works efficiently in learning.Neural Computation, 1998

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.183909Z

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Observation fd8ab8c3-ec7d-41c0-b00c-4fc2096278de · outbound

This paper cites Distributed second-order optimization using kronecker-factored approximations.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Distributed second-order optimization using kronecker-factored approximations

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.173034Z

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Observation fb5cc6da-3356-4ac6-9535-1e70c4e00804 · outbound

This paper cites Gradient descent on neurons and its link to approximate second-order optimization.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Gradient descent on neurons and its link to approximate second-order optimization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.160512Z

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Observation db03ea9b-f366-4beb-a448-779e715d8a9d · outbound

This paper cites Multi- grain: a unified image embedding for classes and instances.ArXiv, 2019.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Multi- grain: a unified image embedding for classes and instances.ArXiv, 2019

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.148698Z

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Observation 2507826a-2b4e-4332-a5f6-cfb53162469e · outbound

This paper cites an unresolved cited work.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:17:11.136375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e279aae1-1835-4dbc-8e70-149fbde4df02 · outbound

This paper cites Li, and Li Fei-Fei.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Li, and Li Fei-Fei

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.126108Z

Source-reported events for the cited work

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Observation 29f0c084-ae66-4b35-a59c-ce920dfd0e75 · outbound

This paper cites an unresolved cited work.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:17:11.115477Z

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Observation f3842598-2fc7-4240-80c1-440c08b00a2f · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature An image is worth 16x16 words: Transformers for image recognition at scale

Reference 8

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Source-reported events for the cited work

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Observation afa57dc8-0175-4c51-86ef-89ff4dbc3b08 · outbound

This paper cites Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.098893Z

Source-reported events for the cited work

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Observation a61b3621-2467-4aea-af47-1d8862517141 · outbound

This paper cites M-FAC: Efficient matrix-free approximations of second-order information.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature M-FAC: Efficient matrix-free approximations of second-order information

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.088216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b3f7c73d-139c-4ff5-b2d0-85e8e904d632 · outbound

This paper cites Practical quasi-newton methods for training deep neural networks.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Practical quasi-newton methods for training deep neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.075885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4f6b391b-fb66-41ca-9d6d-ef9ec3a7f99a · outbound

This paper cites Shampoo: Preconditioned stochastic tensor optimization.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Shampoo: Preconditioned stochastic tensor optimization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.062853Z

Source-reported events for the cited work

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Observation 0483b3c9-5c9c-452b-b839-47e73a804f8c · outbound

This paper cites Deep residual learning for im- age recognition.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Deep residual learning for im- age recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.047835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ce042a25-2eff-45b2-97be-78c979801fa6 · outbound

This paper cites Augment your batch: better training with larger batches.ArXiv, 2019.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Augment your batch: better training with larger batches.ArXiv, 2019

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.034445Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 81b97ce0-b87f-4812-888a-8ed869b860fc · outbound

This paper cites Weinberger.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Weinberger

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.022047Z

Source-reported events for the cited work

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Observation e9d2e296-baf4-44f1-b615-0ac742666e09 · outbound

This paper cites Kingma and Jimmy Ba.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Kingma and Jimmy Ba

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:11.009568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8883a3b-4e46-47ee-880d-cc00a2538cea · outbound

This paper cites Efficient approximations of the fisher matrix in neural networks using kronecker product singular value decomposition.ESAIM: Proceedings and Surveys, 2023.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Efficient approximations of the fisher matrix in neural networks using kronecker product singular value decomposition.ESAIM: Proceedings and Surveys, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.996028Z

Source-reported events for the cited work

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Observation a1dae585-622f-4782-982d-5249fef9a7de · outbound

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

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Learning multiple layers of features from tiny images

Reference 18

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MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 19

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Source-reported events for the cited work

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Observation 72a43a52-db8b-40c4-87c1-4838e415eb63 · outbound

This paper cites Lecun, L.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Lecun, L

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.968227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 610ae801-5e74-4c37-baa0-f87bf4cbdb4c · outbound

This paper cites Turner, and Alireza Makhzani.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Turner, and Alireza Makhzani

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.955338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 026d9955-f059-4d68-9eeb-543d45d4eb42 · outbound

This paper cites Simplifying momentum-based positive-definite submanifold optimization with applications to deep learning.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Simplifying momentum-based positive-definite submanifold optimization with applications to deep learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.942068Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2847cd46-050c-401c-9ccc-5bba07e6db22 · outbound

This paper cites Sophia: A scalable stochastic second-order optimizer for language model pre-training.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Sophia: A scalable stochastic second-order optimizer for language model pre-training

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.929722Z

Source-reported events for the cited work

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Observation ee5c025c-d299-4716-a86f-8e5827735f28 · outbound

This paper cites A layer-wise natural gradient optimizer for training deep neural networks.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature A layer-wise natural gradient optimizer for training deep neural networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.918243Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 372145ab-023f-4386-891a-5526e080c927 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.IEEE/CVF International Conference on Computer Vision (ICCV), 2021.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Swin transformer: Hierarchical vision transformer using shifted windows.IEEE/CVF International Conference on Computer Vision (ICCV), 2021

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.905993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 698d7088-7771-429f-b9f6-98a85e909a8d · outbound

This paper cites Sgdr: Stochastic gradient descent with warm restarts.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Sgdr: Stochastic gradient descent with warm restarts

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.893695Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6da05896-a062-4115-b31b-8a8e61370c8f · outbound

This paper cites Decoupled weight decay regularization.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Decoupled weight decay regularization

Reference 27

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Source-reported events for the cited work

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Observation 8d36b2fb-7a69-49cb-8890-d142446f6854 · outbound

This paper cites Optimizing neural networks with kronecker-factored ap- proximate curvature.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Optimizing neural networks with kronecker-factored ap- proximate curvature

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.874008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d937628b-0db7-40f2-beea-c3935abee7af · outbound

This paper cites Müller and Frank Hutter.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Müller and Frank Hutter

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.861350Z

Source-reported events for the cited work

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Observation 75020cb3-85da-4bc5-84a9-b16435bda0ec · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Pytorch: An imperative style, high-performance deep learning library

Reference 30

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Source-reported events for the cited work

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Observation ddfd595d-431f-496d-b20f-4e5aa7064ae2 · outbound

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MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:17:10.839907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 14cb8fb8-87ea-4a9d-8b35-f62dad079b0c · outbound

This paper cites Rethinking the inception architecture for computer vision.IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2818–2826, 2015.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Rethinking the inception architecture for computer vision.IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2818–2826, 2015

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.828404Z

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Observation 8e785c3d-f706-4c19-8add-9555bd6ed6ca · outbound

This paper cites Skfac: Training neural networks with faster kronecker-factored approximate curvature.IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 13474–13482, 2021.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Skfac: Training neural networks with faster kronecker-factored approximate curvature.IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 13474–13482, 2021

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.816442Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e2719896-dbf9-4c6e-8f44-392f7c85d550 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Training data-efficient image transformers & distillation through attention

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.803775Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a0879d8-3967-40a0-bb81-281976e36854 · outbound

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MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 35

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Observation c193ab2f-cf11-4de7-aa30-e697da1c8380 · outbound

This paper cites Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:17:10.617438Z

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Observation 8829e7ac-587b-447c-8e88-84448e48f7fa · outbound

This paper cites an unresolved cited work.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Unresolved cited work

Reference 37

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Observation 645fcb38-3318-4b6f-b471-d6951f9e7fa5 · outbound

This paper cites Samworth.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Samworth

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.759957Z

Source-reported events for the cited work

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Observation 29cdf730-c136-43d7-b57c-a6cd9575a443 · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Cutmix: Regularization strategy to train strong classifiers with localizable features

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.746626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41823d0b-ade8-4c19-8cbf-3057193a0b28 · outbound

This paper cites Wide residual networks.British Machine Vision Conference, 2016.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Wide residual networks.British Machine Vision Conference, 2016

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.732925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d27baa9-cd46-4761-86c8-08d67421e4ee · outbound

This paper cites Fast convergence of natural gradient descent for overparameterized neural networks, 2019.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Fast convergence of natural gradient descent for overparameterized neural networks, 2019

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.720707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0ef7793-9a4c-48dc-926c-2ef22bc2f106 · outbound

This paper cites Dauphin, and David Lopez-Paz.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Dauphin, and David Lopez-Paz

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.708454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bce84376-017f-4181-b36e-1a73480a10b8 · outbound

This paper cites Eva: Practical second-order optimization with kronecker- vectorized approximation.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Eva: Practical second-order optimization with kronecker- vectorized approximation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.696477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 80a51d15-a37c-4cee-920c-be80f966cff8 · outbound

This paper cites Random erasing data augmentation.AAAI Conference on Artificial Intelligence, 2017.

MAC: An Efficient Gradient Preconditioning using Mean Activation Approximated Curvature Random erasing data augmentation.AAAI Conference on Artificial Intelligence, 2017

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:17:10.683527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

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