Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Why Shallow Networks Struggle to Approximate and Learn High Frequencies
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.17301.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:11:14.945747Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-02T16:47:10.354637Z
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 2f01ed4b-7f35-44fc-ad83-982570df4476 · inbound
Orthogonal greedy algorithm for linear operator learning with shallow neural network cites this paper.
Orthogonal greedy algorithm for linear operator learning with shallow neural network Why Shallow Networks Struggle to Approximate and Learn High Frequencies
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:11:14.945747Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae9bdddb-5cfb-483a-9b52-f501687f32d2 · inbound
Structured First-Layer Initialization Pre-Training Techniques to Accelerate Training Process Based on $\varepsilon$-Rank cites this paper.
Structured First-Layer Initialization Pre-Training Techniques to Accelerate Training Process Based on $\varepsilon$-Rank Why Shallow Networks Struggle to Approximate and Learn High Frequencies
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:06:11.162441Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13e2f5d3-55a5-485e-813d-a67af71cb148 · inbound
Second-Order Path Kernel Interpolation Formulas in Machine Learning cites this paper.
Second-Order Path Kernel Interpolation Formulas in Machine Learning Why Shallow Networks Struggle to Approximate and Learn High Frequencies
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T16:47:10.355899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.