Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How many samples are needed to train a deep neural network?
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.16696.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T08:35:37.953328Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T12:58:08.652374Z
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 aa098f0e-8264-41a8-b7dc-775689f05767 · inbound
How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks cites this paper.
How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks How many samples are needed to train a deep neural network?
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:15:20.008382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2569f223-c3f3-47f8-ad5a-7fec7fd58e5f · inbound
Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records cites this paper.
Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records How many samples are needed to train a deep neural network?
Reference 111
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T12:58:08.654076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.