Pith Number

pith:EFRRHSDO

pith:2026:EFRRHSDOUUUOMGQAIQN7GUAHPN

not attested not anchored not stored refs pending

Order-Agnostic Autoregressive Modelling with Missing Data

Ignacio Peis, Jes Frellsen, Pablo M. Olmos

Order-agnostic autoregressive models can be trained directly on incomplete data to impute values and choose which ones to query next.

arxiv:2605.06355 v2 · 2026-05-07 · cs.LG · stat.ML

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\pithnumber{EFRRHSDOUUUOMGQAIQN7GUAHPN}

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3 Author claim open · sign in to claim

4 Citations open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Across a suite of real-world benchmarks, our Missingness-Aware Order-Agnostic Autoregressive Model (MO-ARM) consistently outperforms established imputation baselines.

C2weakest assumption

The reinterpretation that standard training on fully observed data implicitly performs imputation under an MCAR mechanism, and that the new framework extends this to general missingness mechanisms without introducing bias, holds as stated in the abstract.

C3one line summary

Order-agnostic autoregressive models are extended via a missingness-aware training framework (MO-ARM) that enables direct learning from incomplete data and active information acquisition, outperforming standard imputation methods on real benchmarks.

Receipt and verification

First computed	2026-05-29T02:05:46.188766Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

216313c86ea528e61a00441bf350077b4a2559d78b3820185af1d06ff5d9f57c

Aliases

arxiv: 2605.06355 · arxiv_version: 2605.06355v2 · doi: 10.48550/arxiv.2605.06355 · pith_short_12: EFRRHSDOUUUO · pith_short_16: EFRRHSDOUUUOMGQA · pith_short_8: EFRRHSDO

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/EFRRHSDOUUUOMGQAIQN7GUAHPN \
  | 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: 216313c86ea528e61a00441bf350077b4a2559d78b3820185af1d06ff5d9f57c

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8ca1ce028131d9ef0234263ebf9c6e483cf3b39a2d5c9c9ab9ec9b984ba9f1d0",
    "cross_cats_sorted": [
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-07T14:34:08Z",
    "title_canon_sha256": "493c5d40d49900c4ca68c54cf476c186904122d586c48e470771c5ce8eb9a929"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.06355",
    "kind": "arxiv",
    "version": 2
  }
}