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Paper Citation Record · LEDGER

Randomized Greedy Algorithms for Neural Network Optimization

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2407.17763.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2407.17763 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:11:14.744116Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-10T22:11:15.229773Z

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 6d25dc57-868a-452c-927d-704c6fda19e3 · 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 Randomized Greedy Algorithms for Neural Network Optimization

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:11:15.234621Z

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.

source=pdf_text observed=2026-08-10T22:11:14.744116Z digest=sha256:fd352cf85974af54dc1f6b5091d95af7ca7b709f692a0c87d35fd2236ec97afe