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Paper Citation Record · LEDGER

Easter2.0: Improving convolutional models for handwritten text recognition

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.14879.

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

pith.paper-citation-record.v1
2205.14879 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:44:59.580166Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:58:08.164987Z

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 67e53881-a411-4e40-95e1-b3cd48643cbf · inbound

DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning cites this paper.

DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning Easter2.0: Improving convolutional models for handwritten text recognition

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T16:44:59.580166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:44:59.580166Z digest=sha256:9d913d52df977358a1cc8477fe388a7cff4edf9df62fd43e110a7597f727120f

Observation 8c427679-ccc8-48c9-80c2-460ee5d715f4 · inbound

MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning cites this paper.

MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning Easter2.0: Improving convolutional models for handwritten text recognition

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:58:08.212297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T13:58:03.983070Z digest=sha256:4af2a188f0d47d9ad0cc7beaf227e35f6a9831a74b8cf1d17d6e35b18aa5a30e