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Paper Citation Record · LEDGER

An Empirical Study of Scaling Law for OCR

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2401.00028.

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

pith.paper-citation-record.v1
2401.00028 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:58:59.252425Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:59:00.710920Z

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 e8405c22-c565-442c-95c6-1bd185a68f5e · inbound

Finetuning Vision-Language Models as OCR Systems for Low-Resource Languages: A Case Study of Manchu cites this paper.

Finetuning Vision-Language Models as OCR Systems for Low-Resource Languages: A Case Study of Manchu An Empirical Study of Scaling Law for OCR

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:59:00.784898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T18:58:59.252425Z digest=sha256:071e49401b51e88064bf1ca170c1da8665fea93e2b8e258ce8ffb205551477d3