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Paper Citation Record · LEDGER

DiT: Self-supervised Pre-training for Document Image Transformer

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2203.02378.

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

pith.paper-citation-record.v1
2203.02378 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:43:55.646930Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:06:44.676416Z

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 942dcc73-790c-4f6e-a348-6c193b69fbad · inbound

Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation cites this paper.

Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation DiT: Self-supervised Pre-training for Document Image Transformer

Reference 195

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:06:44.678259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-13T20:06:44.480769Z digest=sha256:cbe5d036aedf38b1f8b45f0559e5200884014b2f1ab96e4bf7862ffd5edcc0ed

Observation 9e9d41b2-3bac-4004-8e3e-3f88f460f0e7 · inbound

TabSniper: Towards Accurate Table Detection & Structure Recognition for Bank Statements cites this paper.

TabSniper: Towards Accurate Table Detection & Structure Recognition for Bank Statements DiT: Self-supervised Pre-training for Document Image Transformer

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T13:43:55.646930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:43:55.646930Z digest=sha256:4cf2cd59122f0cc2397169c1b91c2d216718122be4e8cc694e8f4704c2fd41c9

Observation 940e10ee-762a-4aff-93d6-79c8f2f618d9 · inbound

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends cites this paper.

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends DiT: Self-supervised Pre-training for Document Image Transformer

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T22:17:27.749896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:17:27.749896Z digest=sha256:f08bb74945ac726accbb95db5aa259da7798a84ed1600fe08f46a131d1686c63

Observation 81854035-019b-4f30-a287-97a4586602cd · inbound

Benchmarking Table Extraction from Heterogeneous Scientific PDF Documents cites this paper.

Benchmarking Table Extraction from Heterogeneous Scientific PDF Documents DiT: Self-supervised Pre-training for Document Image Transformer

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-03T21:19:25.250581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:19:25.250581Z digest=sha256:76b55771fdf3a0cee284b9fa77e382fe295720f1c5ddcc50d3b215d63860d3ed

Observation ac84befe-ca00-4e43-a8f5-b538256d48b8 · inbound

Improving Layout Representation Learning Across Inconsistently Annotated Datasets via Agentic Harmonization cites this paper.

Improving Layout Representation Learning Across Inconsistently Annotated Datasets via Agentic Harmonization DiT: Self-supervised Pre-training for Document Image Transformer

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:50:58.283625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T16:28:16.315767Z digest=sha256:5c0508919bfa00e68d116f0cd23928b8c28ecebfe44fdc1f740b97006f40f1d4