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Paper Citation Record · LEDGER

Optimal learning rate schedules in high-dimensional non-convex optimization problems

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2202.04509.

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

pith.paper-citation-record.v1
2202.04509 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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:48:50.480589Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:39:45.044616Z

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 80156d54-db79-46f4-8069-df4302dbccae · inbound

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks cites this paper.

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks Optimal learning rate schedules in high-dimensional non-convex optimization problems

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:50.480589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:48:50.480589Z digest=sha256:dea4b9bca6063f26d3b75eb3fcb5f4cc0d4950fb97dc9ab897ff0b299c18db75

Observation f25371e4-785c-4b18-b5ac-b47287052cdb · inbound

A statistical physics framework for optimal learning cites this paper.

A statistical physics framework for optimal learning Optimal learning rate schedules in high-dimensional non-convex optimization problems

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:39:45.097555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T18:39:39.539635Z digest=sha256:151b56a7baba10f4ee7a3f488ec0887f2a4761c56ecc7f2b7f1cae50628b794d