Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2206.07085.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:11:11.700324Z
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
12
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 1a824798-db9f-445c-bf17-1c4792fad0ac · inbound
Batch Normalization Decomposed cites this paper.
Batch Normalization Decomposed Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:11:11.700324Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b2953767-98e2-4ece-9dd2-5b5a957c2cd8 · inbound
Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks cites this paper.
Wolkowicz-Styan Upper Bound on the Hessian Eigenspectrum for Cross-Entropy Loss in Nonlinear Smooth Neural Networks Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T16:15:34.086154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 60cca88f-78c4-4bee-b393-fe8bb67de7c2 · inbound
Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks cites this paper.
Closed-Form Steepest Descent Direction toward Flat Minima: Reducing Upper Bounds on the Loss Hessian Eigenspectrum in Neural Networks Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T09:44:36.913336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.