Paper Citation Record · LEDGER

An Exponential Learning Rate Schedule for Deep Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:12:03.536337Z

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

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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 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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.