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Paper Citation Record · LEDGER

SGD with Large Step Sizes Learns Sparse Features

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.05337.

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

pith.paper-citation-record.v1
2210.05337 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:47:09.983206Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:48:49.450826Z

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 067a2e78-80a2-4059-bd3d-b882536bdec6 · inbound

AI for the Open-World: the Learning Principles cites this paper.

AI for the Open-World: the Learning Principles SGD with Large Step Sizes Learns Sparse Features

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T11:47:09.983206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:47:09.983206Z digest=sha256:3904e48e27acbba974ef1b66ad17491d0e0dafcc00c426cd52e345b2b535cc39

Observation 3243b1bb-8435-4704-81a1-041a34cd44dd · inbound

SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training cites this paper.

SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training SGD with Large Step Sizes Learns Sparse Features

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:48:49.648252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:48:36.710873Z digest=sha256:7d55a4ac81a945ee726b80b2ebaf0de3207df52ded84d05dd7462a045bbe4bd1