Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1810.07770.
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 2026-08-14T15:13:02.038044Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T14:24:44.880029Z
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 a6d3ebc9-4ddb-427e-83b2-c1f5c1c1ebe1 · inbound
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes cites this paper.
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:13:02.038044Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f4daea6-166e-4e80-acd7-aa9d3aa22e31 · inbound
How much do language models memorize? cites this paper.
How much do language models memorize? Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:35:41.639943Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a2eec40-fba7-47e5-9585-ea72563d0d8f · inbound
MEDAL: Manifold Embedding Distillation via Autoencoder Learning cites this paper.
MEDAL: Manifold Embedding Distillation via Autoencoder Learning Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity
Reference 116
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T14:24:44.881470Z
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.