pith:YQECANQJ
TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering
TabClustPFN clusters any new tabular dataset in one forward pass by amortizing Bayesian inference over assignments and cluster count.
arxiv:2601.21656 v3 · 2026-01-29 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YQECANQJPDNQQY55IBGXIVWEYD}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
Claims
TabClustPFN clusters unseen datasets in a single forward pass, without dataset-specific retraining or hyperparameter tuning, and outperforms classical, deep, and amortized clustering baselines on synthetic and real-world tabular benchmarks.
The synthetic datasets drawn from the flexible clustering prior sufficiently resemble the structure and heterogeneity of real-world tabular data so that the pretrained network generalizes without retraining.
TabClustPFN performs amortized Bayesian inference for cluster assignments and cardinality on unseen tabular data after pretraining on synthetic data from a flexible prior.
Receipt and verification
| First computed | 2026-05-17T23:39:16.532043Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c40820360978db0863bd404d7456c4c0e7ea3a9b1f784bde4f589a642ac46093
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YQECANQJPDNQQY55IBGXIVWEYD \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: c40820360978db0863bd404d7456c4c0e7ea3a9b1f784bde4f589a642ac46093
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "52237989bfe2f9d02b9c67c7377f89fba6d3ce6b1b437e61a8cef3cc7d241419",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2026-01-29T12:56:41Z",
"title_canon_sha256": "1034c67585577229f33c36ca2e3318c2d6b6db96de232b13a1fd0d1331b5ed06"
},
"schema_version": "1.0",
"source": {
"id": "2601.21656",
"kind": "arxiv",
"version": 3
}
}