Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2001.07384.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:27:38.291896Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T19:22:34.812180Z
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 61a9c61d-76fa-4573-b50b-969855e3b1e8 · inbound
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer cites this paper.
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:27:38.291896Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a846dd8-e028-4ee5-ad8d-aa0c10fafebe · inbound
Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs cites this paper.
Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:17:09.234749Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24c46833-6304-417d-b863-8007ac798b53 · inbound
On the Difficulty of Learning a Meta-network for Training Data Selection cites this paper.
On the Difficulty of Learning a Meta-network for Training Data Selection Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T19:22:34.813484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.