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| license: apache-2.0 | |
| tags: | |
| - research-notes | |
| - document-ai | |
| - reading-list | |
| - planning | |
| # 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 artifact | |
| + `README.md` — this documentation | |
| + `config.json` — architecture configuration | |
| + `training_args.json` — default experiment settings | |
| + `model.safetensors` — initialization checkpoint | |
| + `NOTES.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. | |