TFM Library

A curated knowledge base on tabular foundation models (TFMs) — the TabPFN family and everything around it. It keeps two things in one place, for every research project that needs them:

1. All the interesting literature — every collected paper as PDF with a full-text extraction, plus two levels of written digest: per-paper summaries and a cross-paper synthesis of the whole field.
2. All the reference repositories — flat-text snapshots of the upstream implementations (TabPFN, its extensions, finetuning codebases, …) so that "how does the official code actually do X?" is always answerable with a text search, offline, against the exact code the papers shipped.

Scope is strictly tabular foundation models: the PFN/TabPFN lineage, direct TFM competitors, and TFM variants. Benchmarks, ordinary tabular deep learning, and domain applications are deliberately out of scope.

The library is designed to be mounted as a read-only folder inside other projects, so all of them share one consistently maintained copy. It is edited only in its own checkout — never from inside a consuming project. If you are an AI agent, read AGENTS.md before touching anything.

Using this library in a project

It is embedded as a git submodule, so a project always sees one exact, pinned commit of the literature — which is what keeps a result reproducible against the sources as they were when it was produced.

Run everything below in the consuming project (CreditPFN, CreditICL, …), never inside the tfm-library/ folder. One command per line: Windows PowerShell has no &&, so chaining with && is a parser error.

1. Add it to a new project

git submodule add https://github.com/andreasgoethals/TFM_Library.git tfm-library

git commit -m "Add tfm-library as read-only submodule"

Then, optionally, create your project's notes file (the one file you are allowed to add inside the folder — see the read-only rule):

Copy-Item tfm-library\PROJECT_SPECIFIC.template.md tfm-library\PROJECT_SPECIFIC.md

2. Update it to the latest version

Already in the project and you want the newest literature. Read CHANGELOG.md first to see what changed, then run these three, in order:

git submodule update --remote tfm-library

git add tfm-library

git commit -m "Bump tfm-library pin"

The first command only moves the working tree; the new pin is not recorded until you git add and commit. Between the two, git submodule status shows a leading + — that is normal, not an error.

Other things you may need

PowerShell one-liner for the update (uses ; and if ($?), not &&):

git submodule update --remote tfm-library; if ($?) { git add tfm-library; git commit -m "Bump tfm-library pin" }

After a fresh clone of a consuming project, the folder is empty until you populate it:

git submodule update --init

Check which commit a project is pinned to:

git submodule status

Contents

Path	What you'll find
SYNTHESIS.md	Start here. The cross-paper synthesis of the TFM paradigm: lineage timeline (PFNs → TabPFN v1/v2/2.5/3 → scaling / adaptation / extensions), the design axes on which the field varies, recurring weaknesses, open frontiers, and a one-card-per-paper appendix.
SUMMARIES.md	The per-paper tour, chronological: venue, where each paper fits, what it contains, strengths and limitations.
papers/	The PDFs, foldered by year and prefixed with the release month — papers/<year>/<MM>_Author_et_al._Title.pdf — with full-text extractions mirrored under papers/text/ as papers/text/<year>/<same-name>.txt.
REPOSITORIES.md	What each code dump is, why it's kept, and what to grep for when building on it.
repositories/	The flat-text code snapshots themselves (made with gitingest).
PROJECT_SPECIFIC.template.md	Template a consuming project copies to PROJECT_SPECIFIC.md for its own notes.
CHANGELOG.md	Human-readable log of library updates — check it before updating a project's pin.
scripts/	Maintenance tools — see below.

The shared documents are project-neutral by contract: they describe the literature, never any one project's pipeline. Project-specific notes live in that project's own PROJECT_SPECIFIC.md.

How to browse

• "I want to understand the field" → read SYNTHESIS.md top to bottom.
• "What did paper X actually do?" → SUMMARIES.md, or grep the full text in papers/text/<year>/.
• "How does the official implementation handle Y?" → REPOSITORIES.md to pick the right dump, then grep repositories/*.txt by symbol name.

Scripts

Windows PowerShell (one command per line — no &&):

python -m venv .venv

.venv\Scripts\Activate.ps1

pip install -r requirements.txt

Everything is run from the repository root.

scripts/maintain.py — the one command to run

Runs the whole maintenance sweep and prints a single consolidated report: re-dumps the upstream repositories, checks every paper has an up-to-date text extraction, checks whether newer arXiv versions of the papers exist, and checks this library against Zotero.

python scripts/maintain.py                  # full sweep
python scripts/maintain.py --check-only     # change nothing, just report
python scripts/maintain.py --skip repos     # skip the slow dump refresh

scripts/refresh_repositories.py — re-snapshot the code dumps

Overwrites every repositories/*.txt with a fresh gitingest dump of its upstream GitHub source, under the same filename so existing greps keep resolving. Atomic (temp file + swap) with a shrink guard that refuses a new dump smaller than 50 % of the old one.

python scripts/refresh_repositories.py
python scripts/refresh_repositories.py --only NanoTabPFN
python scripts/refresh_repositories.py --force-shrink --only "PFNS.txt"

scripts/extract_paper_text.py — PDF → text

Writes papers/<year>/X.pdf to papers/text/<year>/X.txt, stripping control bytes so the result stays greppable. Step 2 of adding a paper.

python scripts/extract_paper_text.py papers/2026/06_Kong_and_Das_Introducing_TabFM.pdf
python scripts/extract_paper_text.py --all      # fill in anything missing
python scripts/extract_paper_text.py --check    # report gaps, write nothing

scripts/check_zotero_sync.py — Zotero ↔ library consistency

Compares the Zotero collection that mirrors this library against papers/ and reports what diverged: papers in one place but not the other, year/month/title/author mismatches, and missing arXiv IDs or DOIs. Read-only on both sides — it queries a copy of zotero.sqlite and never writes to Zotero or moves a file.

python scripts/check_zotero_sync.py
python scripts/check_zotero_sync.py --collection "Foundation Models"
python scripts/check_zotero_sync.py --json      # machine-readable

scripts/check_paper_versions.py — are the PDFs current?

For every paper with an arXiv ID, asks arXiv whether a newer version exists than the one on disk, and reports the ones worth re-downloading. Never downloads anything itself.

python scripts/check_paper_versions.py

The read-only rule

Inside a consuming project, tfm-library/ is read-only. Never edit, add, move, or delete anything in it — a change there is not tracked by the consuming project's history and is lost the moment the pin moves. Corrections go to this repository's own checkout and flow back down.

The single exception: a project may create PROJECT_SPECIFIC.md inside the folder, by copying PROJECT_SPECIFIC.template.md. That filename is gitignored by the library, so it never dirties the submodule's status and can never be pushed upstream. All project-specific notes about this literature belong there, following the rules in the template.

Housekeeping notes

• repositories/TabPFN Wide.txt (~366 MB) exceeds GitHub's file limit and is gitignored; regenerate locally with python scripts/refresh_repositories.py --only "TabPFN Wide.txt".
• repositories/VSC Documentation.txt is the one deliberate exception to the TFM-only scope, and it is a load-bearing one — do not remove it. It is the full KU Leuven / Flemish Supercomputer Centre user documentation. Every project consuming this library trains and evaluates on VSC, so SLURM scripting, partition and GPU choice, the Lustre/GPFS storage split, and credit accounting are shared questions across all of them; having the answers greppable offline is worth far more than the file costs. No further non-TFM files should be added.
• This repository is public.

Consuming projects

Project	Mountpoint	Since	Angle
CreditPFN	tfm-library/	2026-07	Real-data continued pretraining of TabPFN on a credit corpus (PD + LGD)
CreditICL	tfm-library/	2026-08	Pretraining-prior design: can domain knowledge be encoded in the synthetic prior? Built on TabICL, whose prior generator is open

The two credit projects attack the same problem from opposite ends of design axis (a) in SYNTHESIS.md: CreditPFN adapts a finished model with real data, CreditICL changes what the model is pretrained on in the first place.