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Paper Citation Record · LEDGER

An Exponential Learning Rate Schedule for Deep Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:1910.07454.

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

pith.paper-citation-record.v1
1910.07454 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:51:41.138639Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

44
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9861d039-6f20-454a-93d9-946f68a90952 · inbound

Navigating Label Ambiguity for Facial Expression Recognition in the Wild cites this paper.

Navigating Label Ambiguity for Facial Expression Recognition in the Wild An Exponential Learning Rate Schedule for Deep Learning

Reference 16

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no resolver link, observed 2026-08-07T19:51:41.138639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:51:41.138639Z digest=sha256:46f032689764cbffc286ed07a68bffcefd243ab9e7ae3b24cc9f0dc57875dd16

Observation 9065601f-5e8f-4027-afc4-a080eab58ae7 · inbound

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware cites this paper.

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware An Exponential Learning Rate Schedule for Deep Learning

Reference 37

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no resolver link, observed 2026-08-07T11:12:43.088731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:12:43.088731Z digest=sha256:6f6120145e1ca873a63be2840f32873f908ed5c5286c044c8ca77743752551fd

Observation 66ccd60d-2f71-4b6a-8be3-0647b003832d · inbound

BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing cites this paper.

BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing An Exponential Learning Rate Schedule for Deep Learning

Reference 41

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no resolver link, observed 2026-08-07T11:07:16.003624Z

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source=pdf_text observed=2026-08-07T11:07:16.003624Z digest=sha256:8fdcb903ded15b38d34c69bd3652a5122d40f3fa7f67cdffdecfe7a72c276e35

Observation 06281ab7-9b3c-41ea-863b-feb85b06a267 · inbound

CIS-BWE: Chaos-Informed Speech Bandwidth Extension cites this paper.

CIS-BWE: Chaos-Informed Speech Bandwidth Extension An Exponential Learning Rate Schedule for Deep Learning

Reference 6

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verified exact
arxiv_id, observed 2026-05-22T00:40:51.639835Z

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=pdf_text observed=2026-05-22T00:37:08.364861Z digest=sha256:3d759f20fdca03d6a2958e682364e4284560f765e8a8068ef70f1dd2b17a39ed

Observation 9c2ee32a-94b6-434f-bac1-134b73ef58f3 · inbound

Data-Driven Adaptive Gradient Recovery for Unstructured Finite Volume Computations cites this paper.

Data-Driven Adaptive Gradient Recovery for Unstructured Finite Volume Computations An Exponential Learning Rate Schedule for Deep Learning

Reference 32

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no resolver link, observed 2026-08-06T15:12:03.536337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:12:03.536337Z digest=sha256:7d3d797389f50b5909290aa2153e467cb43f2b4dd618a38ff0732651d3f5a173

Observation baa989bd-c063-468f-b6ad-8b9df202b558 · inbound

Improving Neural Network Training using Dynamic Learning Rate Schedule for PINNs and Image Classification cites this paper.

Improving Neural Network Training using Dynamic Learning Rate Schedule for PINNs and Image Classification An Exponential Learning Rate Schedule for Deep Learning

Reference 25

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no resolver link, observed 2026-08-06T12:28:42.277183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:28:42.277183Z digest=sha256:5a7668d02e29fd95bc620b332f082e8108d0a8e82f8e0cc4eb03cbcb91cae5c7

Observation e88324ab-93e1-47e4-ab61-ab26e9ea07b1 · inbound

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data cites this paper.

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data An Exponential Learning Rate Schedule for Deep Learning

Reference 62

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no resolver link, observed 2026-08-06T11:41:58.595410Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:41:58.595410Z digest=sha256:992f3dd637d4cb8028ea7e67ea2e0ae83c844d5e9243d8e326855f4f03f22632

Observation a7e70c5d-ca58-4e06-8731-23af5144ae74 · inbound

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards cites this paper.

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards An Exponential Learning Rate Schedule for Deep Learning

Reference 19

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no resolver link, observed 2026-08-03T19:38:20.795587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:38:20.795587Z digest=sha256:897b4e12347942b8104bb13805200dd9283862e537ff2e0952bd1ccd40f49e96

Observation ed123b43-a3e8-4bbe-9566-2c76e2078605 · inbound

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards cites this paper.

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards An Exponential Learning Rate Schedule for Deep Learning

Reference 19

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unresolved
no resolver link, observed 2026-08-04T06:47:16.806756Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:47:16.806756Z digest=sha256:5fd118fe8c707abc03113945a7fd29265232592740b81a38280d9236ed76533b

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

Demystifying Manifold Constraints in LLM Pre-training cites this paper.

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

Reference 58

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T17:44:44.438637Z digest=sha256:a1129f86b8da2c4a5418a965acd37883ef9b7b36d6799eec14e426ff7b7e3d11

Observation 07a4976f-5924-4386-8263-0c6bcc556fc7 · inbound

Optimal scenario design for climate emulation cites this paper.

Optimal scenario design for climate emulation An Exponential Learning Rate Schedule for Deep Learning

Reference 235

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verified exact
arxiv_id, observed 2026-06-26T18:49:44.397297Z

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=2026-06-26T18:43:06.382026Z digest=sha256:0bee0367daf3eb712c85267b9b713eba757b45695cd0b946d9940b5ef42ffe86

Observation 261d8098-b02f-475a-a0af-167f974ae1cf · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors An Exponential Learning Rate Schedule for Deep Learning

Reference 162

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metadata mismatch
arxiv_id, observed 2026-07-04T20:30:07.771827Z

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=2026-06-25T20:05:09.179627Z digest=sha256:760b3af50ae1c1e7f4564f483f4f4133be70645e4a3ed772744306d416c3e5ff

Observation 900b21f5-fc8f-4477-be28-2a2c0cc5f588 · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors An Exponential Learning Rate Schedule for Deep Learning

Reference 47

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no resolver link, observed 2026-08-02T10:14:08.553485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T10:14:08.553485Z digest=sha256:14b4523900d954e7b86575543b7720ef258dc9dd93ec2779b5dcde38d37f0267

Observation 6006b382-1d48-4f9e-a0a2-85928852702d · inbound

Path optimization method for the sign problem: Insights from random matrix models cites this paper.

Path optimization method for the sign problem: Insights from random matrix models An Exponential Learning Rate Schedule for Deep Learning

Reference 32

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unresolved
no resolver link, observed 2026-08-01T22:29:30.146859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:29:30.146859Z digest=sha256:6fc2286437588c3bc1c72cf70034b7378e5bafadbbbd752040e824ad771c0d58

Observation 93e607d3-3560-4973-bbc3-58267e82bf76 · inbound

Weight-norm Criticality: A Mechanism for Loss Spikes Induced by the Normalization and Weight Decay cites this paper.

Weight-norm Criticality: A Mechanism for Loss Spikes Induced by the Normalization and Weight Decay An Exponential Learning Rate Schedule for Deep Learning

Reference 8

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no resolver link, observed 2026-08-01T08:50:41.107729Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:50:41.107729Z digest=sha256:dabdea33622061b211379c6b9b02205784cac10dacd80160ab186ad1447c0f93