Toward Document AI (planning notes)
Overview
Reading notes and an experiment sketch for Document AI. The repository emphasizes what still needs to be tested instead of manufacturing scores or release claims.
Feedback on the structure is welcome; the code is intentionally short.
How To Read This Repository
The note follows a intro-related-method-exp-conclusion outline and a narrative-progressive writing style. Plans and hypotheses are kept apart from results; any future numbers should ship with dataset versions, commands, seeds and raw logs.
What Is Covered
- research question scope and likely confounders
- one proposed comparison against matched baselines
- evaluation context such as FUNSD, SROIE, and CORD
- reproducibility checks and open questions
Scope And Limitations
Exploratory by design: no benchmark claims, no completed ablations, no released code, no trained checkpoint. The references are a starting point for verification, not evidence that the study has run.
Open Questions
- which baselines are actually comparable under matched capacity?
- what is the minimum data exposure for a meaningful signal?
- which confounders would invalidate a naive comparison?
Related Work
A reading list around Document AI is being assembled. Entries will be added as the note matures; suggestions via repository discussions are welcome.
Files
analysis.md— primary artifactREADME.md— this documentationconfig.json— architecture configurationtraining_args.json— default experiment settingsmodel.safetensors— initialization checkpointNOTES.md— informal to-do notes
License
Released under apache-2.0. Review the source-data terms separately when this repository is used with external datasets.
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