Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Does Learning Rate Decay Help Modern Neural Networks?
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1908.01878.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:48:45.281153Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T05:40:24.297793Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation faf4f39e-dd6a-4079-a3d0-c9e1dd180e17 · inbound
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training cites this paper.
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training How Does Learning Rate Decay Help Modern Neural Networks?
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:48:45.281153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41315ccb-2f77-488b-a766-2528d8610d77 · inbound
Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation cites this paper.
Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation How Does Learning Rate Decay Help Modern Neural Networks?
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:26:54.041063Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 17e733de-2682-4d03-b49f-1d228acacc83 · inbound
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems cites this paper.
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems How Does Learning Rate Decay Help Modern Neural Networks?
Reference 48
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T20:51:08.901040Z
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.
Observation dfd38cb2-6973-46bd-adf8-f44cc189dfc8 · inbound
Anytime Training with Schedule-Free Spectral Optimization cites this paper.
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
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.
Observation 339cfd79-b8ae-4809-bec7-edbbe738c39b · inbound
Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data cites this paper.
Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data How Does Learning Rate Decay Help Modern Neural Networks?
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:54:33.061955Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.