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Paper Citation Record · LEDGER

Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2505.03577.

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

pith.paper-citation-record.v1
2505.03577 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:46:58.293165Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T20:42:37.093722Z

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 9e9846d9-7e6f-4c6d-9127-c83f5ba04ae1 · inbound

Microscopic and collective signatures of feature learning in neural networks cites this paper.

Microscopic and collective signatures of feature learning in neural networks Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:58.293165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:58.293165Z digest=sha256:21598156ba9b53963849ee5e74f40a92417ef1cc94e8057389fc876ae8eb9cd9

Observation ea342bbd-f5d0-4514-9201-854ebf1a9ade · inbound

Bayesian Inference with Shaped Deep Non-linear MLPs cites this paper.

Bayesian Inference with Shaped Deep Non-linear MLPs Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-28T20:42:37.095578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T20:41:59.878583Z digest=sha256:58e438f46e68a2b4f90cf96ad4924233bafed504e72c2c142c2f1c09b412f2d7