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Paper Citation Record · LEDGER

The boundary of neural network trainability is fractal

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.06184.

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

pith.paper-citation-record.v1
2402.06184 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:43:08.680044Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:43:10.358066Z

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 ac025386-8e78-47e3-b420-663ccce4141c · inbound

The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions cites this paper.

The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions The boundary of neural network trainability is fractal

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:43:10.423646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T00:43:08.680044Z digest=sha256:da067b7d3b79ba7d1c15d64d6895eb08f320d4644011b66ce2f5b23c0edea704

Observation 93310c06-d348-4dca-b722-4524c5a892f4 · inbound

Implicit Bias of SGD in Multivariate ReLU Networks: Effective Width Collapse cites this paper.

Implicit Bias of SGD in Multivariate ReLU Networks: Effective Width Collapse The boundary of neural network trainability is fractal

Reference 120

Resolution
unresolved
no resolver link, observed 2026-07-12T01:11:50.444218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:11:50.444218Z digest=sha256:8de2746fe5aa7b2df43f2ffa61fa3f4b84f4122ce9bc5599f9c84a02bb846d40

Observation 2dd9f7be-b165-4543-805f-f9c7ca376a7b · inbound

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification cites this paper.

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification The boundary of neural network trainability is fractal

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-31T07:42:46.557974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T07:42:46.557974Z digest=sha256:d376f5f66248f04fecffd8c9c31df28126a49b71be82fb2114f2c01f91c430e2

Observation d208ca87-b1eb-4a30-a6fa-78f5ac66a57c · inbound

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification cites this paper.

Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification The boundary of neural network trainability is fractal

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-04T03:23:47.495003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T03:23:47.495003Z digest=sha256:906c240f483df76e1263daa6dcabba13c7793fb86e7080b4ed9b607e415f9e52