Anytime Training with Schedule-Free Spectral Optimization | Paper Citation Record

Observation 67d02533-35c5-4638-b25c-1a26bbf5814d · outbound

This paper cites Springer New York, 2009.isbn: 9780387848587.doi: 10.1007/978-0-387-84858-7.url: http://dx.doi.org/ 10.1007/978-0-387-84858-7.

Anytime Training with Schedule-Free Spectral Optimization Springer New York, 2009.isbn: 9780387848587.doi: 10.1007/978-0-387-84858-7.url: http://dx.doi.org/ 10.1007/978-0-387-84858-7

Reference 1

Resolution: verified exact; doi, observed 2026-05-25T05:40:23.229924Z

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Observation 9aabb2cc-5ff8-42f0-9867-2c7b94c703dd · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:06:58.269281Z

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Observation 8a85edfd-c2a2-4c0e-86ed-c47c167aca36 · outbound

This paper cites Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts.

Anytime Training with Schedule-Free Spectral Optimization Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts

Reference 3

Resolution: verified exact; doi, observed 2026-05-25T05:40:23.233823Z

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Observation 221a12f4-7e15-46c3-8811-0178d95b8eae · outbound

This paper cites Language models are few-shot learners.

Anytime Training with Schedule-Free Spectral Optimization Language models are few-shot learners

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.286494Z

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Observation e5aa6c21-dbde-4fe0-8cfd-03de4c4f015e · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Anytime Training with Schedule-Free Spectral Optimization LLaMA: Open and Efficient Foundation Language Models

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.532456Z

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Observation 4f201f2a-9dff-45b2-bce7-fe03cec0439b · outbound

This paper cites A Survey of Large Language Models.

Anytime Training with Schedule-Free Spectral Optimization A Survey of Large Language Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.503827Z

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Observation 87c0db5d-2d91-48dd-8a04-aad34fe628b4 · outbound

This paper cites Large Language Models: A Survey.

Anytime Training with Schedule-Free Spectral Optimization Large Language Models: A Survey

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.511807Z

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Observation f52fb94d-c78b-4a5b-afed-9875b19345e0 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

Anytime Training with Schedule-Free Spectral Optimization RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.423186Z

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Observation 17e3ec70-d319-4ea3-bde8-9813059afdd8 · outbound

This paper cites A Survey on Vision-Language-Action Models for Embodied AI.

Anytime Training with Schedule-Free Spectral Optimization A Survey on Vision-Language-Action Models for Embodied AI

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.443258Z

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Observation 4892bc6b-ef57-4484-bce0-15fa5d73a10c · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Anytime Training with Schedule-Free Spectral Optimization OpenVLA: An Open-Source Vision-Language-Action Model

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.480379Z

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Observation 724c3f1f-4495-42aa-80a0-0a257583401f · outbound

This paper cites Continual lifelong learning with neural networks: A review.

Anytime Training with Schedule-Free Spectral Optimization Continual lifelong learning with neural networks: A review

Reference 11

Resolution: verified exact; doi, observed 2026-05-25T05:40:23.260375Z

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Observation 4017adeb-12d9-4bb8-a579-e7e9ca2d95f1 · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:06:58.254283Z

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Observation 251165b9-b237-4ec4-a9eb-8b07b7125252 · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

Anytime Training with Schedule-Free Spectral Optimization A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.475359Z

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Observation 1283b2a3-629d-4739-a3c2-a94040d7ab82 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

Anytime Training with Schedule-Free Spectral Optimization Overcoming catastrophic forgetting in neural networks

Reference 14

Resolution: malformed identifier; doi_truncated, observed 2026-05-25T05:40:23.249463Z

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Observation 0199a976-abba-44ac-8f18-043f7ffbcd57 · outbound

This paper cites doi: 10.1109/tpami.2021.3057446.

Anytime Training with Schedule-Free Spectral Optimization doi: 10.1109/tpami.2021.3057446

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-25T05:40:23.255421Z

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Observation fb1c99a0-322b-4d65-8366-52ffb74ba763 · outbound

This paper cites Step-size Optimization for Continual Learning.

Anytime Training with Schedule-Free Spectral Optimization Step-size Optimization for Continual Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.484726Z

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Observation 5eeb1719-cbdc-4b7f-9f0a-d55a1733160e · outbound

This paper cites Anytime Pretraining: Horizon-Free Learning-Rate Schedules with Weight Averaging.

Anytime Training with Schedule-Free Spectral Optimization Anytime Pretraining: Horizon-Free Learning-Rate Schedules with Weight Averaging

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.491763Z

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Observation cf92c9ef-22a9-4f53-89df-75f9fc990e26 · outbound

This paper cites The road less scheduled.

Anytime Training with Schedule-Free Spectral Optimization The road less scheduled

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.256754Z

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Observation 7f427c20-eae5-4e91-ad3e-006e7fe8e863 · outbound

This paper cites How far away are truly hyperparameter-free learning algorithms?.

Anytime Training with Schedule-Free Spectral Optimization How far away are truly hyperparameter-free learning algorithms?

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.428103Z

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Observation 9ac3cbec-f844-4d44-b424-a23272ece849 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Anytime Training with Schedule-Free Spectral Optimization SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.261862Z

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Observation dc25f9dc-fb26-48e5-b3f5-5c4212c40f59 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Anytime Training with Schedule-Free Spectral Optimization Training Compute-Optimal Large Language Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.448291Z

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Observation 9a6f8e3b-48f0-46de-8454-e44d0815df1d · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Anytime Training with Schedule-Free Spectral Optimization MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.464134Z

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Observation 3d0a5eff-72f4-4a3b-a1be-6549605a4382 · outbound

This paper cites A method for solving the convex programming problem with convergence rate O (1/k2).

Anytime Training with Schedule-Free Spectral Optimization A method for solving the convex programming problem with convergence rate O (1/k2)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.314739Z

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Observation f0dc8bfc-599a-4351-bf0a-42873447d8d6 · outbound

This paper cites An optimal method for stochastic composite optimization.

Anytime Training with Schedule-Free Spectral Optimization An optimal method for stochastic composite optimization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.317721Z

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Observation ae44ae5f-2aed-4fca-892a-34785a321ea0 · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:06:58.306969Z

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Observation bc7b8a2f-2565-494d-a659-9a50a5bd435c · outbound

This paper cites Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations.

Anytime Training with Schedule-Free Spectral Optimization Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.418964Z

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Observation e7bd2b19-81d5-452c-b607-0ede6828ea68 · outbound

This paper cites Model Merging in Pre-training of Large Language Models.

Anytime Training with Schedule-Free Spectral Optimization Model Merging in Pre-training of Large Language Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.455637Z

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Observation 734cd0ed-0c2e-45b4-ae39-c37c855cfa57 · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Anytime Training with Schedule-Free Spectral Optimization Averaging Weights Leads to Wider Optima and Better Generalization

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.497687Z

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Observation 97087dc8-858e-40c3-a174-7c77b116ca37 · outbound

This paper cites Accelerating neural network training: An analysis of the AlgoPerf competition.

Anytime Training with Schedule-Free Spectral Optimization Accelerating neural network training: An analysis of the AlgoPerf competition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.302155Z

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Observation 3781e209-7f0e-404a-abc0-4f0591517a7e · outbound

This paper cites Scaling laws and compute-optimal training beyond fixed training durations.

Anytime Training with Schedule-Free Spectral Optimization Scaling laws and compute-optimal training beyond fixed training durations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.292337Z

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Observation 58681d5e-800d-4efe-922b-9265a976f7a8 · outbound

This paper cites Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training.

Anytime Training with Schedule-Free Spectral Optimization Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.296111Z

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Observation a5b054e3-4509-43e1-8ea0-9e677c8bf469 · outbound

This paper cites 2026.url:https://openreview.net/forum?id=Jw7khYzYzl.

Anytime Training with Schedule-Free Spectral Optimization 2026.url:https://openreview.net/forum?id=Jw7khYzYzl

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.299248Z

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Observation c1ae49cb-865d-4077-ae8d-5c4016a2b38c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Anytime Training with Schedule-Free Spectral Optimization Adam: A Method for Stochastic Optimization

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.469368Z

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Observation dd5b4946-474f-4a44-86ac-54def34d78af · outbound

This paper cites Decoupled Weight Decay Regularization.

Anytime Training with Schedule-Free Spectral Optimization Decoupled Weight Decay Regularization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.304630Z

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Observation d7a3e429-7310-46ae-8dfe-73672a02e50f · outbound

This paper cites github.io/posts/muon/.

Anytime Training with Schedule-Free Spectral Optimization github.io/posts/muon/

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.312112Z

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Observation 9da63cbe-e866-4e4f-b9ff-377539f30f36 · outbound

This paper cites GitHub repository, master branch.

Anytime Training with Schedule-Free Spectral Optimization GitHub repository, master branch

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.283791Z

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Observation cbf12a49-d647-4416-8000-59c3de7fd028 · outbound

This paper cites Adamuon: Adaptive muon optimizer.arXiv preprint arXiv:2507.11005.

Anytime Training with Schedule-Free Spectral Optimization Adamuon: Adaptive muon optimizer.arXiv preprint arXiv:2507.11005

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.311145Z

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Observation da4022e0-4eb4-46ff-a5c3-43b3f5f41210 · outbound

This paper cites Normuon: Making muon more efficient and scalable.arXiv preprint arXiv:2510.05491.

Anytime Training with Schedule-Free Spectral Optimization Normuon: Making muon more efficient and scalable.arXiv preprint arXiv:2510.05491

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.265559Z

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Observation 7ad1e7b4-03bb-441d-bdbf-1c5c8a055192 · outbound

This paper cites Dion: Distributed Orthonormalized Updates.

Anytime Training with Schedule-Free Spectral Optimization Dion: Distributed Orthonormalized Updates

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.273862Z

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Observation 8c0e42a4-0e5f-4e7d-9578-5ac6449d3be8 · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:06:58.280980Z

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Observation d1f9dd4e-689a-4dc3-a1b2-7af7df958880 · outbound

This paper cites arXiv preprint arXiv:2512.16928 , year=.

Anytime Training with Schedule-Free Spectral Optimization arXiv preprint arXiv:2512.16928 , year=

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.255336Z

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Observation 6b4f9160-9379-4a8b-adb5-f3d806c73a03 · outbound

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

Anytime Training with Schedule-Free Spectral Optimization Asgo: Adaptive structured gradient optimization.arXiv preprint arXiv:2503.20762

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.260775Z

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Observation 4202fc28-2be3-4ea4-b305-138ef9c2f5c6 · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:06:58.271411Z

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Observation c56a5ba2-4dd0-446e-b9c0-8ea1944c0c4b · outbound

This paper cites Rethinking Language Model Scaling under Transferable Hypersphere Optimization.

Anytime Training with Schedule-Free Spectral Optimization Rethinking Language Model Scaling under Transferable Hypersphere Optimization

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.236309Z

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Observation 4f70ece4-361b-4344-be98-14b1abe311f1 · outbound

This paper cites The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm.

Anytime Training with Schedule-Free Spectral Optimization The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.241637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f702449d-0877-4b3d-9b6a-8dfa10dbcd8d · outbound

This paper cites Muon$^2$: Boosting Muon via Adaptive Second-Moment Preconditioning.

Anytime Training with Schedule-Free Spectral Optimization Muon$^2$: Boosting Muon via Adaptive Second-Moment Preconditioning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.224200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9f8da9b7-a8ef-4bfd-9ed4-e964f327b8a0 · outbound

This paper cites arXiv preprint arXiv:2510.16981 , year=.

Anytime Training with Schedule-Free Spectral Optimization arXiv preprint arXiv:2510.16981 , year=

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.219072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bfd1da3e-5088-489f-b563-00cc80ae8c64 · outbound

This paper cites Ky Fan Norms and Beyond: Dual Norms and Combinations for Matrix Optimization.

Anytime Training with Schedule-Free Spectral Optimization Ky Fan Norms and Beyond: Dual Norms and Combinations for Matrix Optimization

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-06-23T04:13:43.394874Z

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Observation b2bd861a-3e82-474f-a63a-6073cd79519e · outbound

This paper cites Muon is Scalable for LLM Training.

Anytime Training with Schedule-Free Spectral Optimization Muon is Scalable for LLM Training

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.249511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e67cdeb2-97f3-4a86-8145-090ee9807ad5 · outbound

This paper cites Kimi K2.5: Visual Agentic Intelligence.

Anytime Training with Schedule-Free Spectral Optimization Kimi K2.5: Visual Agentic Intelligence

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.278884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5b18ae39-66bb-4075-9cf0-367d2ffc1c64 · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

Anytime Training with Schedule-Free Spectral Optimization GLM-5: from Vibe Coding to Agentic Engineering

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.294930Z

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Observation f2e13eb9-d30a-4278-ab3e-41a2d0883c94 · outbound

This paper cites Singh, L.

Anytime Training with Schedule-Free Spectral Optimization Singh, L

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.305666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e50a045e-4120-444d-b4fe-524039a2b5bc · outbound

This paper cites Empirical Analysis of the Hessian of Over-Parametrized Neural Networks.

Anytime Training with Schedule-Free Spectral Optimization Empirical Analysis of the Hessian of Over-Parametrized Neural Networks

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.319208Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bdf2fd9b-de55-453f-9c2c-af9ff0834f74 · outbound

This paper cites An Investigation into Neural Net Optimization via Hessian Eigenvalue Density.

Anytime Training with Schedule-Free Spectral Optimization An Investigation into Neural Net Optimization via Hessian Eigenvalue Density

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.273521Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7c89e96a-d8b5-4e38-86b5-afd2b87a00df · outbound

This paper cites When do spectral gradient updates help in deep learning?arXiv preprint arXiv:2512.04299.

Anytime Training with Schedule-Free Spectral Optimization When do spectral gradient updates help in deep learning?arXiv preprint arXiv:2512.04299

Reference 55

Resolution: metadata mismatch; arxiv_id, observed 2026-05-25T05:40:24.413339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1b620e58-78fa-470b-81b9-c9e4586f43a6 · outbound

This paper cites The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training.

Anytime Training with Schedule-Free Spectral Optimization The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.438563Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8d8c894c-4621-4d69-a0a5-8d8fcc8d970e · outbound

This paper cites A simple weight decay can improve generalization.

Anytime Training with Schedule-Free Spectral Optimization A simple weight decay can improve generalization

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.278425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation db8dc595-2794-4365-a6d7-96653c9c9a58 · outbound

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

Anytime Training with Schedule-Free Spectral Optimization Why Do We Need Weight Decay in Modern Deep Learning?

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.519091Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0cb985d7-ce27-4841-8b93-9909a7c52a84 · outbound

This paper cites Hyperparameter transfer enables consistent gains of matrix-preconditioned optimizers across scales.

Anytime Training with Schedule-Free Spectral Optimization Hyperparameter transfer enables consistent gains of matrix-preconditioned optimizers across scales

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.387899Z

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Observation 1386eb37-7e9c-45ba-b3cf-1f36c73c8643 · outbound

This paper cites On the Convergence of Muon and Beyond.

Anytime Training with Schedule-Free Spectral Optimization On the Convergence of Muon and Beyond

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.401466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d9dde0a3-d930-47c9-ae2e-fba44b67a9f4 · outbound

This paper cites On the Convergence Analysis of Muon.

Anytime Training with Schedule-Free Spectral Optimization On the Convergence Analysis of Muon

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.345524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b00c8c1e-d3be-4c56-a083-653c7efde4b1 · outbound

This paper cites Convergence Bound and Critical Batch Size of Muon Optimizer.

Anytime Training with Schedule-Free Spectral Optimization Convergence Bound and Critical Batch Size of Muon Optimizer

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-06-09T03:07:01.590146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation de0e3aa4-45dc-4d3e-8fa1-4584cce08d28 · outbound

This paper cites A Note on the Convergence of Muon.

Anytime Training with Schedule-Free Spectral Optimization A Note on the Convergence of Muon

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.354022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3ee0d189-62ad-4671-aa00-b4f1980b6b93 · outbound

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

Anytime Training with Schedule-Free Spectral Optimization Old Optimizer, New Norm: An Anthology

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.336072Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8267c817-5880-460a-9aa3-dc452ab96d33 · outbound

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

Anytime Training with Schedule-Free Spectral Optimization Training Deep Learning Models with Norm-Constrained LMOs

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.361216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 093566bb-d9d4-4404-afee-5be8aee48a0a · outbound

This paper cites Symbolic discovery of optimization algorithms.

Anytime Training with Schedule-Free Spectral Optimization Symbolic discovery of optimization algorithms

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.275836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 93238a18-f7a6-4540-9b12-60593d0f5c68 · outbound

This paper cites Shampoo: Preconditioned Stochastic Tensor Optimization.

Anytime Training with Schedule-Free Spectral Optimization Shampoo: Preconditioned Stochastic Tensor Optimization

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.527641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation af06c929-b330-4528-b2ba-34324b6a7670 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Anytime Training with Schedule-Free Spectral Optimization Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.284758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7649af41-a85f-44e5-a7d0-dbc786496e79 · outbound

This paper cites Why warmup the learning rate? underlying mechanisms and improvements.

Anytime Training with Schedule-Free Spectral Optimization Why warmup the learning rate? underlying mechanisms and improvements

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.289424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3597113d-4245-4936-aff3-fa33bbb30e4c · outbound

This paper cites Learning-rate-free learning by d-adaptation.

Anytime Training with Schedule-Free Spectral Optimization Learning-rate-free learning by d-adaptation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.309669Z

Source-reported events for the cited work

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Observation 07ba298f-8ec4-40ac-bca2-03702ff427be · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

Anytime Training with Schedule-Free Spectral Optimization Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.264580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d667cc57-783f-4636-ac3f-6211c7dfdcdd · outbound

This paper cites GShard: Scaling giant models with conditional computation and automatic sharding.

Anytime Training with Schedule-Free Spectral Optimization GShard: Scaling giant models with conditional computation and automatic sharding

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.267214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c52a1439-7518-4f38-8aa4-55ee3979ecff · outbound

This paper cites Switch Transformers: scaling to trillion parameter models with simple and efficient sparsity.

Anytime Training with Schedule-Free Spectral Optimization Switch Transformers: scaling to trillion parameter models with simple and efficient sparsity

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:06:58.259436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e2df2b38-aae1-4530-962d-b1c83bf6e800 · outbound

This paper cites L2 Regularization versus Batch and Weight Normalization.

Anytime Training with Schedule-Free Spectral Optimization L2 Regularization versus Batch and Weight Normalization

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.369953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 41ab2342-e1d9-4e23-96d5-104b291b08d0 · outbound

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

Anytime Training with Schedule-Free Spectral Optimization Why Gradients Rapidly Increase Near the End of Training

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.375625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 76de1a34-8ab0-4056-b083-46b6444a6dfc · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Anytime Training with Schedule-Free Spectral Optimization Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.380560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation be9dc4e6-b669-4878-8b39-0408b168cd49 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Anytime Training with Schedule-Free Spectral Optimization RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.405967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 702288e3-12f0-4650-bcf9-229a2de7090a · outbound

This paper cites Root Mean Square Layer Normalization.

Anytime Training with Schedule-Free Spectral Optimization Root Mean Square Layer Normalization

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.323889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b92b3a43-0820-419f-af66-e9f00abc0dc5 · outbound

This paper cites ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs.

Anytime Training with Schedule-Free Spectral Optimization ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:24.331701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 00610a37-d084-49bc-8032-ffbe8daaebbc · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:00:42.090072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1aa4e422-a58a-4f3d-aff9-67b8f9290aa9 · outbound

This paper cites 2024.url:https://github.

Anytime Training with Schedule-Free Spectral Optimization 2024.url:https://github

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:00:42.093213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1066c9f0-f270-4d08-8889-9421d6dc335c · outbound

This paper cites an unresolved cited work.

Anytime Training with Schedule-Free Spectral Optimization Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-05-25T11:00:42.086846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d9b1ee6d-add6-4bb5-be52-bc8337f1852f · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Anytime Training with Schedule-Free Spectral Optimization The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:40:24.365491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2b035606-8fee-4a37-a626-930f3ded1fc6 · outbound

This paper cites Language models are unsupervised multitask learners.

Anytime Training with Schedule-Free Spectral Optimization Language models are unsupervised multitask learners

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T11:00:42.080212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b4022916-51ae-42d7-a89d-ecb63214b796 · outbound

This paper cites NVIDIA A100 Tensor Core GPU: Performance and Innovation.

Anytime Training with Schedule-Free Spectral Optimization NVIDIA A100 Tensor Core GPU: Performance and Innovation

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:40:23.239671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3b386363-0cd0-4515-8db0-d0b689d21da4 · outbound

This paper cites PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transforma- tion and Graph Compilation.

Anytime Training with Schedule-Free Spectral Optimization PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transforma- tion and Graph Compilation

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-05-25T05:40:23.245462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation dfd38cb2-6973-46bd-adf8-f44cc189dfc8 · outbound

This paper cites How Does Learning Rate Decay Help Modern Neural Networks?.

Anytime Training with Schedule-Free Spectral Optimization How Does Learning Rate Decay Help Modern Neural Networks?

Reference 87

Resolution: malformed identifier; arxiv_id, observed 2026-05-25T05:40:24.300674Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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