Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2202.08658.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:17:37.001723Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T00:45:12.038820Z
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 a0e59c41-770d-4f7d-951f-88d18a6a2832 · inbound
Feature learning is decoupled from generalization in high capacity neural networks cites this paper.
Feature learning is decoupled from generalization in high capacity neural networks The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:17:37.001723Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f38898a-8768-424c-8fd2-e4a19fb80ca6 · inbound
A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.
A Theory of Saddle Escape in Deep Nonlinear Networks The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:51:05.785136Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 141806b5-0c36-4873-a22c-67b8d13cf1ad · inbound
A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.
A Theory of Saddle Escape in Deep Nonlinear Networks The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T02:25:54.645643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ae5a0ef9-d857-401e-bc88-04c06703a9e0 · inbound
A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.
A Theory of Saddle Escape in Deep Nonlinear Networks The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T00:45:12.041148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.