Pith. sign in

Paper Citation Record · LEDGER

A Random Matrix Approach to Neural Networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1702.05419.

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

pith.paper-citation-record.v1
1702.05419 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:14:22.981694Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-01T15:35:47.565241Z

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 7a39be40-7c36-4fe6-8e14-4961e16d527f · inbound

Deep ReLU networks -- injectivity capacity upper bounds cites this paper.

Deep ReLU networks -- injectivity capacity upper bounds A Random Matrix Approach to Neural Networks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T00:14:22.981694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:22.981694Z digest=sha256:b4d6f2d073b4da7872a46afee4551a334845893ebb851ca7f3b2b7f4ada51417

Observation 0ffd8982-e3fd-4d85-afd0-066ad58ca38c · inbound

Spectral phase transitions and trainability in neural network learning dynamics cites this paper.

Spectral phase transitions and trainability in neural network learning dynamics A Random Matrix Approach to Neural Networks

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-07-01T15:35:47.566947Z

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.

source=pdf_text observed=2026-06-30T01:22:17.359656Z digest=sha256:af9147618119f36d1a961062a566819db919841be4bb36ad31c1e563674bf9fa