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Paper Citation Record · LEDGER

LionVote: Per-Layer Learning Rate Adaptation for Lion

As of 21 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.09266.

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

pith.paper-citation-record.v1
2607.09266 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T04:17:58.962415Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8cbeb75d-54bd-407e-b200-5cb587aa8cc2 · outbound

This paper cites W., Pfau, D., Schaul, T., Shillingford, B., and de Freitas, N.

LionVote: Per-Layer Learning Rate Adaptation for Lion W., Pfau, D., Schaul, T., Shillingford, B., and de Freitas, N

Reference 1

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:951e116d701538e957eab3608c62409473847592e13da6bd197cb8ae098eec9c

Observation a25c34a1-1b4b-42a0-934a-2484819e7bfd · outbound

This paper cites signSGD : Compressed optimisation for non-convex problems.

LionVote: Per-Layer Learning Rate Adaptation for Lion signSGD : Compressed optimisation for non-convex problems

Reference 2

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:5957cca1c1bbd807bdb4455b3c00387d9ae6c985df392d35ded4b61edce46c9f

Observation 5bdcdcfa-fd1c-4836-9257-62c448bfac8e · outbound

This paper cites an unresolved cited work.

LionVote: Per-Layer Learning Rate Adaptation for Lion Unresolved cited work

Reference 3

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no resolver link, observed 2026-07-13T04:17:58.962415Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:13707e16175e67cdedf51c3ae0f95a508657f27a437a29c724d7995b6da285b8

Observation f6d98635-3bc1-4f66-bd4a-12b8920293a5 · outbound

This paper cites Z., and Talwalkar, A.

LionVote: Per-Layer Learning Rate Adaptation for Lion Z., and Talwalkar, A

Reference 4

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:b39af9b13663a2b0b1ef8b9c8907266bb5e9d8b02c8148283fe2a32bbd06d228

Observation 70787327-038a-456b-bae0-314679f04184 · outbound

This paper cites and Mishchenko, K.

LionVote: Per-Layer Learning Rate Adaptation for Lion and Mishchenko, K

Reference 5

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:6aca0d2d056d77c7394b0b77a64409a68632affeeea94fb3c119e15f649ebea1

Observation c3eef540-d207-4514-83a2-3e8c98749e23 · outbound

This paper cites The road less scheduled.

LionVote: Per-Layer Learning Rate Adaptation for Lion The road less scheduled

Reference 6

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:8acb85a76e36a994a601c2251214b867b39f7e0307b2e3601ac18eb77854e6a4

Observation ba9c237d-58c4-43d8-a5b2-868dd2fb934b · outbound

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

LionVote: Per-Layer Learning Rate Adaptation for Lion An image is worth 16x16 words: Transformers for image recognition at scale

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:f7b7c42aa58a9861b65e6815abc0350c211b70ec3954246a35046e1b8506f592

Observation 08cf2aab-f2b3-4e81-9178-8056e98fc953 · outbound

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

LionVote: Per-Layer Learning Rate Adaptation for Lion Adaptive subgradient methods for online learning and stochastic optimization

Reference 8

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:ad5ff215266a479a03b803f4e92920b9b7cdee21e8960d1adabb8260e4f43fc1

Observation c79e9384-e9e9-428c-ac9d-26edfcdc1110 · outbound

This paper cites Deep residual learning for image recognition.

LionVote: Per-Layer Learning Rate Adaptation for Lion Deep residual learning for image recognition

Reference 9

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:18b4f65cd5112c98072443b2a77337fb474e065884406a7720001a5523bd20bd

Observation 4f3828e8-d530-4011-9151-3ab64144bf3d · outbound

This paper cites Noise-adaptive layerwise learning rates: Accelerating geometry-aware optimization for deep neural network training.

LionVote: Per-Layer Learning Rate Adaptation for Lion Noise-adaptive layerwise learning rates: Accelerating geometry-aware optimization for deep neural network training

Reference 10

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:f01c8d2779a8e8a31a9629d0fafeef6043d2d8049e96b1f4abbb78058ec79fc2

Observation 4db50434-f295-4ccb-9b54-85a1307e4a6c · outbound

This paper cites and Ruder, S.

LionVote: Per-Layer Learning Rate Adaptation for Lion and Ruder, S

Reference 11

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:436f8b78413ca8e27ab777836162a74eecc7da5771fabde42d70f3839825c38c

Observation 06a976f0-f5bc-4e5a-83ef-8f5eb0e1c079 · outbound

This paper cites Muon: An optimizer for hidden layers in neural networks.

LionVote: Per-Layer Learning Rate Adaptation for Lion Muon: An optimizer for hidden layers in neural networks

Reference 12

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:8c960392f21c8d1c63e1c1ca4ce2b6428f2d47c7bf65715f7d0cf9451e4eef5d

Observation 8110590f-a14b-43e2-b304-8267cd8fde8c · outbound

This paper cites an unresolved cited work.

LionVote: Per-Layer Learning Rate Adaptation for Lion Unresolved cited work

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:2a2b2ab4d901df86e19e3812e5e4d5b6dec49476bd7875433b60f706bb80b10e

Observation 6e190b7d-e15c-4c28-8802-d27bbc39398d · outbound

This paper cites Cautious optimizers: Improving training with one line of code.

LionVote: Per-Layer Learning Rate Adaptation for Lion Cautious optimizers: Improving training with one line of code

Reference 14

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:074244a08390cc8db1a8ba6dd467094cf025d7523ea5291a3fdb1618640e36ad

Observation 03d906d2-8255-4f6f-92c7-f7c5afb7113b · outbound

This paper cites and Hutter, F.

LionVote: Per-Layer Learning Rate Adaptation for Lion and Hutter, F

Reference 15

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:02ae43a9ee87e70c4f41d52ccf7678eeb69e1aa999f0db02a49612a9f04f7db4

Observation 933195f3-a949-4f29-abd7-513c4181c0f2 · outbound

This paper cites and Hutter, F.

LionVote: Per-Layer Learning Rate Adaptation for Lion and Hutter, F

Reference 16

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:1f8f8315536d68c82c250de06289f911e6b6de4eee45501e1f1d573ff1757d0f

Observation 3fd542f2-6995-43d6-a295-1606c06ae251 · outbound

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

LionVote: Per-Layer Learning Rate Adaptation for Lion PyTorch : An imperative style, high-performance deep learning library

Reference 17

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:cbf6e442a5b40511c9be1d9652efe1cb255d58e796812bc8541548a76993f5ee

Observation 2f8aa75b-f52d-4c33-8878-41e9c90174c3 · outbound

This paper cites An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes.

LionVote: Per-Layer Learning Rate Adaptation for Lion An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes

Reference 18

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:0b7b2edb8c810f6262264b5177e75d6cab788a3c5fc85e4dfc321d11da12c989

Observation e959b445-3a50-4007-a07d-6cc5159f9fa0 · outbound

This paper cites M., Schneider, F., and Hennig, P.

LionVote: Per-Layer Learning Rate Adaptation for Lion M., Schneider, F., and Hennig, P

Reference 19

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:f539248f840b28120e58d3e60f4739a305de660ca867c0d90f722fc44cda40b1

Observation 2fb2fa15-5ce9-4da5-885e-850f11a83116 · outbound

This paper cites N., Kaiser, L., and Polosukhin, I.

LionVote: Per-Layer Learning Rate Adaptation for Lion N., Kaiser, L., and Polosukhin, I

Reference 20

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:848410181b3eae427d659a1a7fd7136143f4cce015baf2a7287bd7d14ef9f20f

Observation 08f26162-caec-4d28-932a-a891112e0e4c · outbound

This paper cites AutoDrop : Training deep learning models with automatic learning rate drop.

LionVote: Per-Layer Learning Rate Adaptation for Lion AutoDrop : Training deep learning models with automatic learning rate drop

Reference 21

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:fef48dfe024164bc314920d5fc946405e9f67a3073805725b23036a0dac93295

Observation 3753eee2-05cc-4415-96a8-1515526e9942 · outbound

This paper cites Large Batch Training of Convolutional Networks.

LionVote: Per-Layer Learning Rate Adaptation for Lion Large Batch Training of Convolutional Networks

Reference 22

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:d49173ec64dc43266ee7e9deb1a79df4b5dd5abeb721adae7cac34c559c7f51a

Observation 8bff8c94-5546-4ab1-844a-34b1016ae3e4 · outbound

This paper cites Large batch optimization for deep learning: Training BERT in 76 minutes.

LionVote: Per-Layer Learning Rate Adaptation for Lion Large batch optimization for deep learning: Training BERT in 76 minutes

Reference 23

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:962a0398a25e37c93b34812a73b43d22d682868e8bc6a5976afdd8534816d651

Observation d75d1813-ca1e-414e-b112-a713f5e00568 · outbound

This paper cites and Komodakis, N.

LionVote: Per-Layer Learning Rate Adaptation for Lion and Komodakis, N

Reference 24

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:0e67c94ec4b1c932eec5d6e7da853b1949628e59c969405cc7c81b6dd13ca21c

Observation 28f9fdb4-e44b-4966-b24c-0d1186f6183a · outbound

This paper cites Deconstructing what makes a good optimizer for autoregressive language models.

LionVote: Per-Layer Learning Rate Adaptation for Lion Deconstructing what makes a good optimizer for autoregressive language models

Reference 25

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source=arxiv_source observed=2026-07-13T04:17:58.962415Z digest=sha256:3371d69635741f7446bb0d4ae8cf4c575e4b856909a0f1f486e80ed5a73f08e0

Pith citing papers

No inbound Pith citation observations are available.