Demystifying Manifold Constraints in LLM Pre-training | Paper Citation Record

Observation 2edf1d9a-72ea-4f0c-ba09-bb40edbef06b · outbound

This paper cites Towards a principled Muon under µP: Ensuring spectral conditions throughout training.

Demystifying Manifold Constraints in LLM Pre-training Towards a principled Muon under µP: Ensuring spectral conditions throughout training

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.929972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f363a3d0-b430-4554-b7a5-3da65af97e6a · outbound

This paper cites an unresolved cited work.

Demystifying Manifold Constraints in LLM Pre-training Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-26T06:51:52.483921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6b2fe08c-42bf-40ee-9555-ed2f704d64ed · outbound

This paper cites Enhancing LLM Training via Spectral Clipping.

Demystifying Manifold Constraints in LLM Pre-training Enhancing LLM Training via Spectral Clipping

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-29T03:04:38.016704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7d1f369c-b63c-4a95-a88d-1a8628111b1f · outbound

This paper cites Learning in transformers under spectral constraints.

Demystifying Manifold Constraints in LLM Pre-training Learning in transformers under spectral constraints

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.475747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dc75a3c6-2f8e-49b5-b814-69e58bd4b179 · outbound

This paper cites Gu and Z.

Demystifying Manifold Constraints in LLM Pre-training Gu and Z

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.921338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 22bbd0f4-7dd4-4051-9246-b3fbd7fe5b99 · outbound

This paper cites Preston Hess, Franz Cesista, Andrii Zahorodnii, Jeremy Bernstein, and Phillip Isola.

Demystifying Manifold Constraints in LLM Pre-training Preston Hess, Franz Cesista, Andrii Zahorodnii, Jeremy Bernstein, and Phillip Isola

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.480067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f2fdbb4-9694-4761-a904-6566ee8eaba6 · outbound

This paper cites Controlled llm training on spectral sphere.

Demystifying Manifold Constraints in LLM Pre-training Controlled llm training on spectral sphere

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.934741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c71b0d1e-814f-4c4c-8bd7-5c74bc985cbb · outbound

This paper cites Yang and L.

Demystifying Manifold Constraints in LLM Pre-training Yang and L

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.587142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7865ece1-9e1a-4d14-8173-720d484dd899 · outbound

This paper cites Hewa Koneputugodage, Shamane Siriwardhana, Violetta Shevchenko, Karol Pajak, James Snewin, Gil Avra- ham, and Alexander Long.

Demystifying Manifold Constraints in LLM Pre-training Hewa Koneputugodage, Shamane Siriwardhana, Violetta Shevchenko, Karol Pajak, James Snewin, Gil Avra- ham, and Alexander Long

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.645451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a68b708f-6fc0-4b99-a6b3-d9af5b393a12 · outbound

This paper cites Fastest descent on a manifold: 4.

Demystifying Manifold Constraints in LLM Pre-training Fastest descent on a manifold: 4

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.439194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 09c41a83-192e-49b8-aa89-3722763acba5 · outbound

This paper cites Fastest descent on a manifold: 2.

Demystifying Manifold Constraints in LLM Pre-training Fastest descent on a manifold: 2

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.435441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0793d9ef-d358-48d7-9729-98e6aa61d848 · outbound

This paper cites Fantastic pretraining optimizers and where to find them 2.1: Hyperball optimization, 12 2025.

Demystifying Manifold Constraints in LLM Pre-training Fantastic pretraining optimizers and where to find them 2.1: Hyperball optimization, 12 2025

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.423926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e266651a-8234-43d9-bcf9-5ab41df08fd8 · outbound

This paper cites 20251026.

Demystifying Manifold Constraints in LLM Pre-training 20251026

Reference 13

Resolution: malformed identifier; doi, observed 2026-05-08T17:53:53.527487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 408581a2-dc72-411a-84f1-8420598191c5 · outbound

This paper cites Decoupled Weight Decay Regularization.

Demystifying Manifold Constraints in LLM Pre-training Decoupled Weight Decay Regularization

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:08.881578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 366a7266-7668-49cf-a79c-f180b3c32392 · outbound

This paper cites Why Gradients Rapidly Increase Near the End of Training.

Demystifying Manifold Constraints in LLM Pre-training Why Gradients Rapidly Increase Near the End of Training

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.661283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9631de9-1045-4c3f-8e86-bec4201236ff · outbound

This paper cites Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks.

Demystifying Manifold Constraints in LLM Pre-training Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.501233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 14948cf7-0c8f-4a68-bcee-0d11c06b91ab · outbound

This paper cites On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.

Demystifying Manifold Constraints in LLM Pre-training On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.810342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2072564f-7d72-4eee-ade2-ba9051136fb3 · outbound

This paper cites Why Do We Need Weight Decay in Modern Deep Learning?.

Demystifying Manifold Constraints in LLM Pre-training Why Do We Need Weight Decay in Modern Deep Learning?

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.583373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bb710117-a561-487c-83a4-55310c6ed413 · outbound

This paper cites Muon: An optimizer for hidden layers.

Demystifying Manifold Constraints in LLM Pre-training Muon: An optimizer for hidden layers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.427948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8bc50449-f5c9-4c5d-be18-6bc338bcc274 · outbound

This paper cites Lower bounds for non-convex stochastic optimization.Mathematical Programming, 199(1):165–214.

Demystifying Manifold Constraints in LLM Pre-training Lower bounds for non-convex stochastic optimization.Mathematical Programming, 199(1):165–214

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.420028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9ff0d42-59cb-4e8a-967f-d52b207404a4 · outbound

This paper cites A Spectral Condition for Feature Learning.

Demystifying Manifold Constraints in LLM Pre-training A Spectral Condition for Feature Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.473359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 44824dad-55d7-438a-a2e5-9d09348ef448 · outbound

This paper cites Beyond MuP: 2.

Demystifying Manifold Constraints in LLM Pre-training Beyond MuP: 2

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.447800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b5ba9518-75ad-40c0-aac7-d3693c1d75df · outbound

This paper cites Limit of the smallest eigenvalue of a large dimensional sample covariance matrix.Ann.

Demystifying Manifold Constraints in LLM Pre-training Limit of the smallest eigenvalue of a large dimensional sample covariance matrix.Ann

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.460611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7cb0bbc8-4f33-4882-85d8-26a019ad4572 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Demystifying Manifold Constraints in LLM Pre-training Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:19:17.426681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bb793abc-6fc0-4d81-8b62-60b442c81c24 · outbound

This paper cites Group normalization.

Demystifying Manifold Constraints in LLM Pre-training Group normalization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.472002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36e054fb-1769-4e98-9536-d10b7e8f6890 · outbound

This paper cites Layer Normalization.

Demystifying Manifold Constraints in LLM Pre-training Layer Normalization

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:08.531365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae70157d-5f2d-4c1d-bfe9-d20607f06a27 · outbound

This paper cites Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks.

Demystifying Manifold Constraints in LLM Pre-training Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.617421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 334cb2e1-6280-4a31-9dfc-11adcb15a98b · outbound

This paper cites Micro-Batch Training with Batch-Channel Normalization and Weight Standardization.

Demystifying Manifold Constraints in LLM Pre-training Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.558335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e385f67-8ece-466f-b8ec-66c37519b53e · outbound

This paper cites Root Mean Square Layer Normalization.

Demystifying Manifold Constraints in LLM Pre-training Root Mean Square Layer Normalization

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-17T18:45:27.296410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70d3bedb-7961-485e-ae56-7cf0911f4c85 · outbound

This paper cites Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization.

Demystifying Manifold Constraints in LLM Pre-training Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.510347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 47cd698e-528b-448b-ab5d-ba04040821ef · outbound

This paper cites Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate.

Demystifying Manifold Constraints in LLM Pre-training Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.775984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5f9d1096-05ab-4e6d-bdc3-a93e902870d3 · outbound

This paper cites The rotation of eigenvectors by a perturbation.

Demystifying Manifold Constraints in LLM Pre-training The rotation of eigenvectors by a perturbation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.431721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e748474a-95c1-462a-81d1-fa0e49ab9f9f · outbound

This paper cites Perturbation bounds in connection with singular value decomposition.BIT Numerical Mathematics, 12(1):99–111.

Demystifying Manifold Constraints in LLM Pre-training Perturbation bounds in connection with singular value decomposition.BIT Numerical Mathematics, 12(1):99–111

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.452135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fe219d6-5dc0-4e13-85ce-631291a4c87f · outbound

This paper cites Training Deep Learning Models with Norm-Constrained LMOs.

Demystifying Manifold Constraints in LLM Pre-training Training Deep Learning Models with Norm-Constrained LMOs

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:22:37.653978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3efc946-0e67-4b2a-95b0-aae07c5a574a · outbound

This paper cites Purifying shampoo: Investigating shampoo’s heuristics by decomposing its preconditioner.arXiv preprint arXiv:2506.03595.

Demystifying Manifold Constraints in LLM Pre-training Purifying shampoo: Investigating shampoo’s heuristics by decomposing its preconditioner.arXiv preprint arXiv:2506.03595

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.684182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3d19e898-3c75-41c9-b9ce-e4ba2158a845 · outbound

This paper cites Shampoo: Preconditioned stochastic tensor optimization.

Demystifying Manifold Constraints in LLM Pre-training Shampoo: Preconditioned stochastic tensor optimization

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.395672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00ad15c4-bcf3-460e-90f7-e35711778238 · outbound

This paper cites Eschenhagen, A.

Demystifying Manifold Constraints in LLM Pre-training Eschenhagen, A

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.493123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f7799bca-5bf9-4092-bb26-3a19778cd3b2 · outbound

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

Demystifying Manifold Constraints in LLM Pre-training A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.604600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 24dc1065-dee6-4fa2-b3b5-d68d9e0649c8 · outbound

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

Demystifying Manifold Constraints in LLM Pre-training Old Optimizer, New Norm: An Anthology

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:27:53.041705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 48ba7c26-ab2f-4df0-9f6b-61b279f49ebc · outbound

This paper cites Asgo: Adaptive structured gradient optimization.arXiv preprint arXiv:2503.20762.

Demystifying Manifold Constraints in LLM Pre-training Asgo: Adaptive structured gradient optimization.arXiv preprint arXiv:2503.20762

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.902107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7c1ad9e-fe70-49b7-82be-fedba31a45a1 · outbound

This paper cites SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training.

Demystifying Manifold Constraints in LLM Pre-training SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.611550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eeca4c05-e80d-49d1-9015-de8493d9bb24 · outbound

This paper cites Memory-Efficient LLM Pretraining via Minimalist Optimizer Design.

Demystifying Manifold Constraints in LLM Pre-training Memory-Efficient LLM Pretraining via Minimalist Optimizer Design

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T02:03:26.475417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 391ef415-473d-4a19-8e64-4f451a34688e · outbound

This paper cites On the width scaling of neural optimizers under matrix operator norms i: Row/column normalization and hyperparameter transfer.arXiv preprint arXiv:2603.09952.

Demystifying Manifold Constraints in LLM Pre-training On the width scaling of neural optimizers under matrix operator norms i: Row/column normalization and hyperparameter transfer.arXiv preprint arXiv:2603.09952

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.724980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 903bcba7-1617-42cb-b2b1-21f27dad111d · outbound

This paper cites Gradient Multi-Normalization for Stateless and Scalable LLM Training.

Demystifying Manifold Constraints in LLM Pre-training Gradient Multi-Normalization for Stateless and Scalable LLM Training

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.860137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0860afa-dc5a-4f18-8b2f-e6378657ab43 · outbound

This paper cites Spectral normalization for generative adversarial networks.

Demystifying Manifold Constraints in LLM Pre-training Spectral normalization for generative adversarial networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.406703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9c39cf46-d2e2-42c4-ac89-ef64fe7c6322 · outbound

This paper cites Learning by Turning: Neural Architecture Aware Optimisation.

Demystifying Manifold Constraints in LLM Pre-training Learning by Turning: Neural Architecture Aware Optimisation

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.654531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2f6df2fc-544a-4582-b3a9-75b4789c61fe · outbound

This paper cites nGPT: Normalized Transformer with Representation Learning on the Hypersphere.

Demystifying Manifold Constraints in LLM Pre-training nGPT: Normalized Transformer with Representation Learning on the Hypersphere

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.766353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ecdaad71-b785-4e3c-8e5a-6fb3a020a2d9 · outbound

This paper cites Nemotron-Flash: Towards latency-optimal hybrid small language models.

Demystifying Manifold Constraints in LLM Pre-training Nemotron-Flash: Towards latency-optimal hybrid small language models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.431827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f7620bf9-b3b5-48b4-b6da-ae9a753636bd · outbound

This paper cites Franke, Urs Spiegelhalter, Marianna Nezhurina, Jenia Jitsev, Frank Hutter, and Michael Hefenbrock.

Demystifying Manifold Constraints in LLM Pre-training Franke, Urs Spiegelhalter, Marianna Nezhurina, Jenia Jitsev, Frank Hutter, and Michael Hefenbrock

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.818862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 19052610-360e-42db-adb7-926ec3095fc3 · outbound

This paper cites Spherical motion dynamics: Learning dynamics of normalized neural network using SGD and weight decay.

Demystifying Manifold Constraints in LLM Pre-training Spherical motion dynamics: Learning dynamics of normalized neural network using SGD and weight decay

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.415246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a156c684-80ab-49d3-92e0-910006558488 · outbound

This paper cites Rehg, and Le Song.

Demystifying Manifold Constraints in LLM Pre-training Rehg, and Le Song

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.387715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 66bf8d64-5567-40e0-ac50-ee0dc73278b5 · outbound

This paper cites Artificial kuramoto oscillatory neurons.

Demystifying Manifold Constraints in LLM Pre-training Artificial kuramoto oscillatory neurons

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.464755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6c3cb6b5-e020-4d53-8d77-4a8c21c5713e · outbound

This paper cites Artificial Kuramoto Oscillatory Neurons.

Demystifying Manifold Constraints in LLM Pre-training Artificial Kuramoto Oscillatory Neurons

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.449352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dd5bd31f-d93b-4f95-adca-ea91093cc2d2 · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models.

Demystifying Manifold Constraints in LLM Pre-training Analyzing and improving the training dynamics of diffusion models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.391753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 72d77f85-8ffc-44fc-a565-78f10d6dac32 · outbound

This paper cites Variance Control via Weight Rescaling in LLM Pre-training.

Demystifying Manifold Constraints in LLM Pre-training Variance Control via Weight Rescaling in LLM Pre-training

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.623547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7ada0e78-bf35-4a2f-84dd-d1be243ebf2f · outbound

This paper cites Three Mechanisms of Weight Decay Regularization.

Demystifying Manifold Constraints in LLM Pre-training Three Mechanisms of Weight Decay Regularization

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.907128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation daee681e-3656-4608-8807-bb987c87a5bd · outbound

This paper cites Understanding AdamW through Proximal Methods and Scale-Freeness.

Demystifying Manifold Constraints in LLM Pre-training Understanding AdamW through Proximal Methods and Scale-Freeness

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.793766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c6751a95-31bf-4211-9702-2f6b1432e5dc · outbound

This paper cites An Exponential Learning Rate Schedule for Deep Learning.

Demystifying Manifold Constraints in LLM Pre-training An Exponential Learning Rate Schedule for Deep Learning

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:08.896788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 546e3c95-58fc-4962-bf6e-5719fd4409ba · outbound

This paper cites AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights.

Demystifying Manifold Constraints in LLM Pre-training AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.579398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dec1ef61-f772-48cb-bf0d-2377857ca165 · outbound

This paper cites L2 Regularization versus Batch and Weight Normalization.

Demystifying Manifold Constraints in LLM Pre-training L2 Regularization versus Batch and Weight Normalization

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.747351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9aac8c65-2157-402a-bbc4-ac7fd291b559 · outbound

This paper cites Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training.

Demystifying Manifold Constraints in LLM Pre-training Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.665048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c1c9885-2ef3-443e-8c19-ed4a7fab8d88 · outbound

This paper cites Beyond MuP: 4.

Demystifying Manifold Constraints in LLM Pre-training Beyond MuP: 4

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.410667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a02ed98c-dee5-4f21-936c-a708ea5cda0f · outbound

This paper cites Lion Secretly Solves Constrained Optimization: As Lyapunov Predicts.

Demystifying Manifold Constraints in LLM Pre-training Lion Secretly Solves Constrained Optimization: As Lyapunov Predicts

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:08.459960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 59619866-3f41-4ff0-bbd6-f0b3aca06c2a · outbound

This paper cites Nonsmooth analysis of singular values.

Demystifying Manifold Constraints in LLM Pre-training Nonsmooth analysis of singular values

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.468444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e32bee35-8c6c-4881-abc1-4986194f55a8 · outbound

This paper cites Smooth manifolds.

Demystifying Manifold Constraints in LLM Pre-training Smooth manifolds

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.374880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 624c48f3-62de-4947-b5fa-fa88bc301705 · outbound

This paper cites Horn and Charles R.

Demystifying Manifold Constraints in LLM Pre-training Horn and Charles R

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.443871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4838c6c9-1d05-4331-a2ba-9975bdd1d3d3 · outbound

This paper cites Sampling from large matrices: An approach through geometric functional analysis.Journal of the ACM, 54(4):21:1–21:19.

Demystifying Manifold Constraints in LLM Pre-training Sampling from large matrices: An approach through geometric functional analysis.Journal of the ACM, 54(4):21:1–21:19

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.379789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 160ea377-4666-486d-a381-b738a460bcb2 · outbound

This paper cites an unresolved cited work.

Demystifying Manifold Constraints in LLM Pre-training Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-05-26T06:51:52.399856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4fd66625-00d3-4658-8957-93eab7134f17 · outbound

This paper cites NanoChat: The best ChatGPT that $100 can buy.

Demystifying Manifold Constraints in LLM Pre-training NanoChat: The best ChatGPT that $100 can buy

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:51:52.384014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 84743629-e181-4906-b22c-3c96fc17f218 · outbound

This paper cites Adaptive Rotational Equilibrium under Spectral Sphere.

Demystifying Manifold Constraints in LLM Pre-training Adaptive Rotational Equilibrium under Spectral Sphere

Reference 70

Resolution: malformed identifier; raw_fallback, observed 2026-05-26T06:51:52.456276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers