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Paper Citation Record · LEDGER

Revisiting ResNets: Improved Training and Scaling Strategies

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2103.07579.

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

pith.paper-citation-record.v1
2103.07579 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:23:02.555835Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 1bb7c129-ecc7-452f-991c-1c4589ecb1cd · inbound

SketchMamba: A Lightweight State-Space Model for Joint Progressive Sketch Classification and Stroke Auto-Completion cites this paper.

SketchMamba: A Lightweight State-Space Model for Joint Progressive Sketch Classification and Stroke Auto-Completion Revisiting ResNets: Improved Training and Scaling Strategies

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-30T18:22:25.429717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T18:22:25.429717Z digest=sha256:c056310b4f8426749d0b5237d0219470dfaeaba29a56ec155820b8c2ee20b0b6

Observation 89299c68-a38a-4cfa-9611-4fd19c25ab18 · inbound

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation cites this paper.

Exploring Budgeted Image Classification with Content-Sensitive Resource Allocation Revisiting ResNets: Improved Training and Scaling Strategies

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-31T23:23:02.555835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:23:02.555835Z digest=sha256:84c68898432ba2464b2fff48b1ba844e5aebd95a640f56f53b2cc7a418f78fb2