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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

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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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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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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

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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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Observation 51c93680-6c3b-423e-b9c2-a43edafc0d98 · outbound

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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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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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=sha256:5c302bcdd24a088b7a819c0ec9b517c5379c4c8845fb6a6746ac000c89848b3e

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=sha256:8bfb6e9eb4b34d4016c2f705afd3b2f2b8425e78e96574a74964ce28d5533907

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:cdb3e34c21be49a80030ae2e81c18e35941c07672e73fda747567acbe51bf94a

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:aa338ae0a6b9c4ce6c66815dd002fe4a36ed5c801ef61f4b7316a0417155bcce

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=sha256:2ae90b9ecf404354688afa8b45b0b0cd839e41f160c931e07d3ec611e446798c

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=sha256:1cf1c82ff88072d967ca9b0d3b4ddcb28b61f83c2d58fa0749a4e2f320e9f58b

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:b1e23061ab922e1fb35ee3e11045bf18952a5f307b2a6eaea900b9852797803b

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=sha256:0a8f24cd4ccdfe5453b572790983d74b4df2e75a7975fdba4d6a45fd8785bbd9

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=sha256:66425be132c5077d589a055ec55d7c8e8fe18b7153e8154c0027c265e6ea2038

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:b8cbc1bde0286f0beb935a66420527eb6c51260cb9c02a3ddcdbe7b8343dd99b

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:e96e936959339d6a161c326bc2d1a39ec04c9f673b801ba7a15165b0de4ac6fd

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=sha256:3e192587d4d0ea45fc82180b12295a48cfcf81701f098fd1e48c7b441a976bff

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=sha256:3bd6c4e003b92c974ae921978f7f281f1fa69e09f0f42134071cd61f84d63cb3

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=sha256:1041e86664b9527205cafda43fbc6bfaac1ab9ab0dfb2ac75e88969e1541920b

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=sha256:5a7353061f7e7ce6acb70dec89e8b5c8d153c08a660c571bcd1416fbc8d1580d

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:a7c9644682a12807d6ca17a4f1ff6609c1a66f3d7b5ca8a090c78b88da3e173e

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:bb79e0fd1ce334e061a9181484e238c0d2b418ad7532c6d509ddbd6249f8883f

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=sha256:712d53e805060b8fc92d6af36c35a3e3ee825fbdba47b29322859e5ea69f2432

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=sha256:19dfdb71e73c68a5564e469ae7a8ba29176a7217538493833fed601b10099ce1

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:a81a7cadff07cd92ddf647cdcec77dac64fecc7e021d36c0c4f46694932720cd

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:b71354162037f0999cb100e6bb31cd821f57e34c230a0f865242d9fe0bc0c2fd

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=sha256:370b3475ce5e7be9c7cf429e3cfc85d1fa779399ffcd19a78d8cf04fce46ea9a

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=sha256:6013476d07f1871d171e043f7ed15d04c218bd5a546997444bcd8c9c676682c4

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:ab027dae46fae45d3f17b3e59d69d88254ba5e169a3db30ff736e3410a8d6078

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=sha256:5097734bc18c723e758f14e40343169a15cc6b69e0de403b53b848306754b3a6

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:b223a58933587f24ddfc439350cbe3b65c46313cce6e3974edb59aa4306399b6

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=sha256:6e85aabe323c2ec7e0f1e2aa07607aae5e0d912142b14d071ed0857ccb94d7f4

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:ac1689f7aac3ca9b696c7fb9e8d32e2de43e44d4d4640125f04330725105d7e6

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=sha256:721bc756f79f3ed38858c078ea4b42ca9865f0a3fca6233e1ad025db1da5e1a2

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=sha256:1c859c95fdfb972c346f21e099f8f22e4a5586876d99f59cad557a4a6302bda0

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=sha256:5900346ffcb0d34f6d8c82d878aa6c0b6a7c8eb016d741e46cd549e5ec100882

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=sha256:79426baae51b14fcb6561d9c3bd1f0d9382539dd0ee2490c35c0047433612f91

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=sha256:072a42183dec128b3a151a9f35310e6af909efe17b4e99cce4d99144386e7cca

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:b99ae7ef3631d5a8cfd302e733b84c356844e588e776a251c902416b7e4b19b6

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=sha256:4145fd1ea18438251128b51dba23628feb7e013e3fd0630c99656ee1345f81bf

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:d30a562d0a1b13b93e7a8db3deec3b70147ae339af2cc383f82096221b6acb8f

Pith citing papers

No inbound Pith citation observations are available.