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Paper Citation Record · LEDGER

Spectral-factorized Positive-definite Curvature Learning for NN Training

As of 9 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2502.06268.

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

pith.paper-citation-record.v1
2502.06268 v3

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

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measured 72 of 72 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

72 of 72 outbound references displayed

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External citation measurements

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Outbound references

Observation d516fe53-433f-42f1-9386-2e893b3b7b03 · outbound

This paper cites write newline.

Spectral-factorized Positive-definite Curvature Learning for NN Training write newline

Reference 1

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Observation 37413ba1-3c82-4b0d-a097-391378fb0cd4 · outbound

This paper cites Optimization algorithms on matrix manifolds.

Spectral-factorized Positive-definite Curvature Learning for NN Training Optimization algorithms on matrix manifolds

Reference 2

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Observation c4db66ff-bcb0-46a3-936f-d056de873a1b · outbound

This paper cites Efficient full-matrix adaptive regularization.

Spectral-factorized Positive-definite Curvature Learning for NN Training Efficient full-matrix adaptive regularization

Reference 3

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Observation ca5bc144-a454-47bc-97b4-0d2edeba16e8 · outbound

This paper cites Learning rate grafting: Transferability of optimizer tuning.

Spectral-factorized Positive-definite Curvature Learning for NN Training Learning rate grafting: Transferability of optimizer tuning

Reference 4

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Observation d84ea81d-27e2-4982-9214-dcaf111bb66d · outbound

This paper cites Natural gradient works efficiently in learning.

Spectral-factorized Positive-definite Curvature Learning for NN Training Natural gradient works efficiently in learning

Reference 5

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Observation ea743440-49b2-421d-9cce-490e99bad129 · outbound

This paper cites Information geometry and its applications, volume 194.

Spectral-factorized Positive-definite Curvature Learning for NN Training Information geometry and its applications, volume 194

Reference 6

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Observation 00e2c0a0-7921-4570-9563-a03e45f402ca · outbound

This paper cites Scalable Second Order Optimization for Deep Learning.

Spectral-factorized Positive-definite Curvature Learning for NN Training Scalable Second Order Optimization for Deep Learning

Reference 7

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Observation b9c04a15-7dc6-4cc4-a748-cab14c7c14b2 · outbound

This paper cites Old Optimizer, New Norm: An Anthology.

Spectral-factorized Positive-definite Curvature Learning for NN Training Old Optimizer, New Norm: An Anthology

Reference 8

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Observation 9c6fa4ac-c613-48d0-b3c6-cad7b79de2a0 · outbound

This paper cites Better plain ViT baselines for ImageNet-1k.

Spectral-factorized Positive-definite Curvature Learning for NN Training Better plain ViT baselines for ImageNet-1k

Reference 9

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Observation c41f817e-9a1c-4a8a-a5dd-24d5a9608ed2 · outbound

This paper cites Manopt, a matlab toolbox for optimization on manifolds.

Spectral-factorized Positive-definite Curvature Learning for NN Training Manopt, a matlab toolbox for optimization on manifolds

Reference 10

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Observation 49abba08-f9fe-463c-8d02-ae60413aecd2 · outbound

This paper cites S., Sra, S., and Tropp, J.

Spectral-factorized Positive-definite Curvature Learning for NN Training S., Sra, S., and Tropp, J

Reference 11

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Observation bfb5ef71-6a46-4399-9b00-2dec1431e214 · outbound

This paper cites Closing the generalization gap of adaptive gradient methods in training deep neural networks.

Spectral-factorized Positive-definite Curvature Learning for NN Training Closing the generalization gap of adaptive gradient methods in training deep neural networks

Reference 12

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Observation 7615c643-16ed-474f-ad7f-04698c8c0a9e · outbound

This paper cites Symbolic Discovery of Optimization Algorithms.

Spectral-factorized Positive-definite Curvature Learning for NN Training Symbolic Discovery of Optimization Algorithms

Reference 13

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Observation c0e3e54d-d70d-4a47-999c-20c17f630a06 · outbound

This paper cites Z., Huang, J., Reich, S., and Stuart, A.

Spectral-factorized Positive-definite Curvature Learning for NN Training Z., Huang, J., Reich, S., and Stuart, A

Reference 14

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Observation 262b1a58-0d27-4111-bb45-9f3713acef7d · outbound

This paper cites On Empirical Comparisons of Optimizers for Deep Learning.

Spectral-factorized Positive-definite Curvature Learning for NN Training On Empirical Comparisons of Optimizers for Deep Learning

Reference 15

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Observation a44f0adb-6656-4b28-a66d-59000abda482 · outbound

This paper cites and Mehta, H.

Spectral-factorized Positive-definite Curvature Learning for NN Training and Mehta, H

Reference 16

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Observation 94d03f1e-902c-4587-b65c-e32c24bc1a72 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

Spectral-factorized Positive-definite Curvature Learning for NN Training Adaptive subgradient methods for online learning and stochastic optimization

Reference 17

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Observation 0c9def5e-bff6-46b8-95d2-e17d763db378 · outbound

This paper cites Proposal of distance-weighted exponential natural evolution strategies.

Spectral-factorized Positive-definite Curvature Learning for NN Training Proposal of distance-weighted exponential natural evolution strategies

Reference 18

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Observation 0032d898-44e8-4844-ac23-fd404ffc5334 · outbound

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Spectral-factorized Positive-definite Curvature Learning for NN Training Exponential natural evolution strategies

Reference 19

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Observation 9f1f57e1-317d-4c0c-bf4b-460f4d558ec2 · outbound

This paper cites Natural gradient variational bayes without fisher matrix analytic calculation and its inversion.

Spectral-factorized Positive-definite Curvature Learning for NN Training Natural gradient variational bayes without fisher matrix analytic calculation and its inversion

Reference 20

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Observation e790a1eb-1253-405d-997c-947d814fdca2 · outbound

This paper cites Shampoo: Preconditioned Stochastic Tensor Optimization.

Spectral-factorized Positive-definite Curvature Learning for NN Training Shampoo: Preconditioned Stochastic Tensor Optimization

Reference 21

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Observation 88f86604-c7b3-4cdf-8260-90fe4f59457c · outbound

This paper cites K., and Gao, J.

Spectral-factorized Positive-definite Curvature Learning for NN Training K., and Gao, J

Reference 22

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Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 23

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This paper cites NanoGPT (124M) quality in 8.2 minutes.

Spectral-factorized Positive-definite Curvature Learning for NN Training NanoGPT (124M) quality in 8.2 minutes

Reference 24

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Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

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This paper cites E., Nielsen, D., Tangkaratt, V., Lin, W., Gal, Y., and Srivastava, A.

Spectral-factorized Positive-definite Curvature Learning for NN Training E., Nielsen, D., Tangkaratt, V., Lin, W., Gal, Y., and Srivastava, A

Reference 26

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Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 27

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This paper cites Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport.

Spectral-factorized Positive-definite Curvature Learning for NN Training Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport

Reference 28

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Observation cbfbca9e-dfc5-4ef3-a529-b9b8bbd460f7 · outbound

This paper cites Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks.

Spectral-factorized Positive-definite Curvature Learning for NN Training Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks

Reference 29

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Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 30

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Observation 9701ce43-72f9-4f7c-8846-a2c03c91fe3c · outbound

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Spectral-factorized Positive-definite Curvature Learning for NN Training Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform

Reference 31

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Spectral-factorized Positive-definite Curvature Learning for NN Training Preconditioned stochastic gradient descent

Reference 32

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This paper cites E., and Schmidt, M.

Spectral-factorized Positive-definite Curvature Learning for NN Training E., and Schmidt, M

Reference 33

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Observation 221cef9f-1fe2-4649-8cfb-ad280f9f81bd · outbound

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Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 34

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Spectral-factorized Positive-definite Curvature Learning for NN Training M., and Schmidt, M

Reference 35

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Observation 3fcaa1b1-fb2c-484d-bf17-2aaaa7df3e02 · outbound

This paper cites E., and Schmidt, M.

Spectral-factorized Positive-definite Curvature Learning for NN Training E., and Schmidt, M

Reference 36

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Observation dcb09d83-3130-494d-8a13-281bf898245e · outbound

This paper cites E., and Makhzani, A.

Spectral-factorized Positive-definite Curvature Learning for NN Training E., and Makhzani, A

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.080428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.259785Z digest=sha256:56bbe44814dabb51b051002ac17f96de27d96f6d32644dbb614e87b7b336723f

Observation d1ff73d5-fed1-4f72-bc32-107140871d21 · outbound

This paper cites Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training.

Spectral-factorized Positive-definite Curvature Learning for NN Training Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.263627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.263627Z digest=sha256:44f8b14a4728d8f5ddaea668f8a18f2c124239900a03dbe4fd7f1d7f505e449e

Observation aa3e3da1-5d1d-49f0-a52a-472240fdd597 · outbound

This paper cites M., Paull, L., Xiong, L., Song, L., and Weller, A.

Spectral-factorized Positive-definite Curvature Learning for NN Training M., Paull, L., Xiong, L., Song, L., and Weller, A

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.067863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.267941Z digest=sha256:3ccd1fd3acc52b92648deb72bee70b7a301ed32cfcf2148e800565f288c370f5

Observation 71b17889-1f39-4b49-91d1-1374354c56a8 · outbound

This paper cites Optimizing millions of hyperparameters by implicit differentiation.

Spectral-factorized Positive-definite Curvature Learning for NN Training Optimizing millions of hyperparameters by implicit differentiation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.054950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.271522Z digest=sha256:884f0f3bc7bffdb2693aa6fddcf107603d8a7597ed8f9943d5c6c2acaafd62ca

Observation 40b8ec48-0b30-4e23-92ae-559af5f0822d · outbound

This paper cites Decoupled Weight Decay Regularization.

Spectral-factorized Positive-definite Curvature Learning for NN Training Decoupled Weight Decay Regularization

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.275513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.275513Z digest=sha256:49d3745742a3d0974a96c88d0ff9e28104334708feb20e37ec6b545495f56d48

Observation b3a7781b-536f-4795-bcc0-f136e6b7a69f · outbound

This paper cites Lecture Notes: Mathematical Modelling of DNA.

Spectral-factorized Positive-definite Curvature Learning for NN Training Lecture Notes: Mathematical Modelling of DNA

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.041692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.279885Z digest=sha256:282d956bb3504e9f33d2a6897ab53d11f7a2b7e8baa55a0e2f5c22ef9a309e0e

Observation 48c1f793-94a8-4f7b-bbab-9770694628fb · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-08T16:15:23.028316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.284116Z digest=sha256:b0efbff6d6c9c5a59f0b9bb2ac1659a0e9ee7efcf2a029701434c08e3f72132d

Observation ae16ffee-619a-49b2-9cd7-e227a5a31cc6 · outbound

This paper cites and Grosse, R.

Spectral-factorized Positive-definite Curvature Learning for NN Training and Grosse, R

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.012780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.288236Z digest=sha256:d501ff55ffd1906da9b9ab3c5cfab8a96470b219eb46e8ac35e8b4ee90331b44

Observation f17a77a8-3322-4558-8a8c-fddbf8951010 · outbound

This paper cites Mixed precision training.

Spectral-factorized Positive-definite Curvature Learning for NN Training Mixed precision training

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:23.001186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.292353Z digest=sha256:6b8c1dd11caed7daa8822008ec1aad74686e3b494ba86d9637e52450f91dac2a

Observation 58f6880a-ca02-4bd0-bce6-3ff394159dfa · outbound

This paper cites and Archambeau, C.

Spectral-factorized Positive-definite Curvature Learning for NN Training and Archambeau, C

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.987915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.296972Z digest=sha256:8acd86cdb5f43180e855cbcb2e3bc1446364dfd48f68c65f8bc5b5e8b988d8cc

Observation f8ae8b2c-a2cb-4e82-867c-0c4d73fb565c · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-08T16:15:22.975280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.302124Z digest=sha256:ba41ed64807030767577cf024a43131fdea603d430ddf6ea92c66f92a60d91b2

Observation 57ca8511-4dd2-41aa-a0ea-253a2fb68655 · outbound

This paper cites B., Pedersen, M.

Spectral-factorized Positive-definite Curvature Learning for NN Training B., Pedersen, M

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.962144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.306084Z digest=sha256:d9c82c4ae6eb6d23819718d61030823e429b662b4369e1a93248f21c69f4a9e5

Observation c1a29769-998a-4b1b-98f4-5188fa456bef · outbound

This paper cites Controlling text-to-image diffusion by orthogonal finetuning.

Spectral-factorized Positive-definite Curvature Learning for NN Training Controlling text-to-image diffusion by orthogonal finetuning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.950305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.309853Z digest=sha256:d788ce2a24e89ad3756f7b3ea679d2a298a637ca6126e3cd8dd4054090fe48fe

Observation 4910e34a-e02b-4c1e-9156-c94d82b65170 · outbound

This paper cites and Goldfarb, D.

Spectral-factorized Positive-definite Curvature Learning for NN Training and Goldfarb, D

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.938132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.314993Z digest=sha256:bd151fa4ff9ab323d4c48ee5af2cddcff30adeb3c00ec4ca9d1e93041d6cb499

Observation d4d9bc23-e920-4c46-a91a-4351ef49f056 · outbound

This paper cites Topmoumoute online natural gradient algorithm.

Spectral-factorized Positive-definite Curvature Learning for NN Training Topmoumoute online natural gradient algorithm

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.924444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.319971Z digest=sha256:83c692704778b77de72c4695630a58bec984421d8a76f056e3f67c07d5c2401a

Observation 0bed36cc-740f-4e70-a97f-9e59a8bb8767 · outbound

This paper cites Hiera: A hierarchical vision transformer without the bells-and-whistles.

Spectral-factorized Positive-definite Curvature Learning for NN Training Hiera: A hierarchical vision transformer without the bells-and-whistles

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.911091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.324628Z digest=sha256:0f0fb7350aedae1a42297dedb319cc9cdab0af699e29d7bfd2d423410dd5caf4

Observation 25ae04b8-a9d5-4a3b-8dc3-e035189877dd · outbound

This paper cites Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models.

Spectral-factorized Positive-definite Curvature Learning for NN Training Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.896822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.328481Z digest=sha256:eafc52bf1b96c5ff163a9e9540b17f48a6d3e5d0663f0af68d2168ac5be3ab0a

Observation 94265aaf-654f-43e5-9518-debed1819096 · outbound

This paper cites Variational Learning is Effective for Large Deep Networks.

Spectral-factorized Positive-definite Curvature Learning for NN Training Variational Learning is Effective for Large Deep Networks

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.332674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.332674Z digest=sha256:409f6a8062408a5f447eb4a81daf06a5e4adf2904fc4ce0f1e2a185d764ddb09

Observation a5ee00b1-8cf5-4761-bc55-477f7dd8b99e · outbound

This paper cites A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale.

Spectral-factorized Positive-definite Curvature Learning for NN Training A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.336710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.336710Z digest=sha256:a85fb2da0e3fcb5d4a6cd76c39193dd68ecb45194df6d38cc1f1d978c445f9ad

Observation 508c6753-bc7d-4df4-b82f-bf397a2db88c · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-08T16:15:22.883048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.341785Z digest=sha256:476b4da6ecac352144ff1f4d94c01194a03fbe757fbe5a46fda19ea218205c7b

Observation 8b52138f-430a-4a20-8762-1113f292dde4 · outbound

This paper cites Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation.

Spectral-factorized Positive-definite Curvature Learning for NN Training Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-08T16:15:22.573647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.345804Z digest=sha256:858eae80c6ec06d7ecdd0a8b7d9a9d992120ce79353d6a82f8eae450c72fc74e

Observation 83b96c36-73e7-493c-9ee5-199a5e93837b · outbound

This paper cites and Hinton, G.

Spectral-factorized Positive-definite Curvature Learning for NN Training and Hinton, G

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.868880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.350467Z digest=sha256:019e14c9c4222bebefb78a0bf3b11d92f58a8ec82cdce70c52352e9b0667535b

Observation bf389409-905e-4f2b-a8f6-243ac71fec16 · outbound

This paper cites H., and Nguyen, D.

Spectral-factorized Positive-definite Curvature Learning for NN Training H., and Nguyen, D

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.855781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.354539Z digest=sha256:5bce4598cd806e81262cb3330f3705fe126303bebb2c0ec7546f89b96cc5779a

Observation 9ce8ecdc-9a00-49d0-9a2d-df1e63d66bc5 · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-08T16:15:22.842598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.358604Z digest=sha256:5ac7f10b1c5f718f2c278d671e9ea28d6b9485b890abb003a1d61e6cd9c21ba1

Observation fbacb41b-212c-40d6-99bf-708bc6ee40dc · outbound

This paper cites Invariance properties of the natural gradient in overparametrised systems.

Spectral-factorized Positive-definite Curvature Learning for NN Training Invariance properties of the natural gradient in overparametrised systems

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.827737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.362478Z digest=sha256:abe229a4f52c6a4595321682a5261ae493d439ff4c8dcaef6f9758877b9022e0

Observation 44adf111-4888-4f8c-8bff-40c19ff7da16 · outbound

This paper cites SOAP: Improving and Stabilizing Shampoo using Adam.

Spectral-factorized Positive-definite Curvature Learning for NN Training SOAP: Improving and Stabilizing Shampoo using Adam

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.366670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.366670Z digest=sha256:a5c369faeeb69d3a31b34178db2ac1d8929cd811528d0869d5fbd853288d3aab

Observation 5d049ff4-1172-42c2-9bef-ab7c8f335e17 · outbound

This paper cites Natural evolution strategies.

Spectral-factorized Positive-definite Curvature Learning for NN Training Natural evolution strategies

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.813559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.370902Z digest=sha256:6c454717dad587e9eaf0b743cb09d4e913899d4ab4ad02436eb641539e827cfe

Observation c2691899-b9fb-41bb-bee3-a8b33a115cd4 · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.374922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.374922Z digest=sha256:78b7d1edb8d9be4c204d56411e9acd7a3a31f4f6cfca56fc459bbb315b8bdcf6

Observation bf0e4f03-f66b-4ce9-957c-5496a186889b · outbound

This paper cites J., Chun, S., Choe, J., and Yoo, Y.

Spectral-factorized Positive-definite Curvature Learning for NN Training J., Chun, S., Choe, J., and Yoo, Y

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.379246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.379246Z digest=sha256:79bdf97f59ba7fe3a2772cf941c3917a1142ba441ad9a626d7d5fed6cd0a240e

Observation aaa2e5af-25a1-43c2-acb9-f5c52582ef4d · outbound

This paper cites Noisy natural gradient as variational inference.

Spectral-factorized Positive-definite Curvature Learning for NN Training Noisy natural gradient as variational inference

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:15:22.782559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T16:15:07.383551Z digest=sha256:79f9bb826487765d2b17875b06d1862e3ecae358196e9e048adc2e77e1728f11

Observation 1a6bc752-0ecb-4ebb-8765-4616954ef9ef · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Spectral-factorized Positive-definite Curvature Learning for NN Training mixup: Beyond Empirical Risk Minimization

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.387966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.387966Z digest=sha256:6693944b87973e9312937bcfa0e218536104e825fb3ee312ba9f928c865ebc1e

Observation 1b8b188b-e946-4551-9ced-bbb0eb046cee · outbound

This paper cites P., Veit, A., Kim, S., Reddi, S., Kumar, S., and Sra, S.

Spectral-factorized Positive-definite Curvature Learning for NN Training P., Veit, A., Kim, S., Reddi, S., Kumar, S., and Sra, S

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.393216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.393216Z digest=sha256:d6ec95254d3328faad4325d742d80851857dfed99194682d676058ca95f2c7c5

Observation f01a9f2a-5a2d-4ef5-a118-3ce50a59f375 · outbound

This paper cites Why Transformers Need Adam: A Hessian Perspective.

Spectral-factorized Positive-definite Curvature Learning for NN Training Why Transformers Need Adam: A Hessian Perspective

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.397282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.397282Z digest=sha256:447e23afa5c0e569be65bcd49ccc0d263570d693d6f6976a2dab524eb92038a2

Observation d5997082-c6bd-435a-b92c-8f8bae59f180 · outbound

This paper cites @esa (Ref.

Spectral-factorized Positive-definite Curvature Learning for NN Training @esa (Ref

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.402681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.402681Z digest=sha256:d380a8f991f3579d65e82c4ba3691fff3077b7105a8e19bd9a7789691e092d25

Observation 6c5288ed-3836-4da0-8208-9d84eabb415d · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.409213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.409213Z digest=sha256:34738edfdb6a25eaec34bdf24868b91b7a5e7c7aed6049ef93e01848825d1cb3

Observation 33f15f5c-6b30-48d6-8348-f68aa9ea2d46 · outbound

This paper cites an unresolved cited work.

Spectral-factorized Positive-definite Curvature Learning for NN Training Unresolved cited work

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-08T16:15:07.414107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:15:07.414107Z digest=sha256:795162aab7207ea73666d271368b6c7f2ce7ea47ad562b3452c2c40e3264d055

Pith citing papers

No inbound Pith citation observations are available.