Pith Number

pith:4AFFH5ZO

pith:2026:4AFFH5ZOLJAPPXRLMCLKQT4V5A

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Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models

Camille No\^us, Denis Cornet, Gregory Beurier, Lauriane Rouan, Robin Reiter

Operator-adaptive models that fold preprocessing selection inside calibration outperform standard PLS and Ridge on most NIRS datasets.

arxiv:2605.13587 v1 · 2026-05-13 · stat.ML · cs.LG · eess.SP

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Claims

C1strongest claim

Compact operator-adaptive PLS with ASLS branch preprocessing achieved a median RMSEP/PLS ratio of 0.960 with 42 wins on 57 datasets, while a deployable AOM-Ridge selector improved over tuned Ridge by a median 2.22% with 35 wins on 52 datasets.

C2weakest assumption

That treating nonlinear or sample-adaptive corrections (SNV, MSC, ASLS) as fold-local branches fully prevents information leakage while still allowing the model to adaptively select effective preprocessing without introducing bias or overfitting to the specific dataset splits.

C3one line summary

Operator-adaptive PLS and Ridge models internalize preprocessing selection via linear operators and fold-local branches, achieving median RMSEP/PLS ratio of 0.960 on 57 datasets and 2.22% improvement over tuned Ridge on 52 datasets.

References

54 extracted · 54 resolved · 0 Pith anchors

[1] Kowalski , abstract = 1986 · doi:10.1016/0003-2670(86)80028-9

[2] Pls-regression: a basic tool of chemometrics 2001 · doi:10.1016/s0169-7439(01)00155-1

[3] Simpls: an alternative approach to partial least squares regression 1993

[4] Hoerl and Robert W 1970 · doi:10.1080/00401706.1970.10488634

[5] Review of the most common pre-processing techniques for near-infrared spectra 2009 · doi:10.1016/j.trac.2009.07.007

Receipt and verification

First computed	2026-05-18T02:44:23.132509Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e00a53f72e5a40f7de2b6096a84f95e82bb1fd01106a9f8946b1ef558ce12d6f

Aliases

arxiv: 2605.13587 · arxiv_version: 2605.13587v1 · doi: 10.48550/arxiv.2605.13587 · pith_short_12: 4AFFH5ZOLJAP · pith_short_16: 4AFFH5ZOLJAPPXRL · pith_short_8: 4AFFH5ZO

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/4AFFH5ZOLJAPPXRLMCLKQT4V5A \
  | 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: e00a53f72e5a40f7de2b6096a84f95e82bb1fd01106a9f8946b1ef558ce12d6f

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "78db40950582b1cef379628dd31244c0819021c541401447a504683bd7a126e4",
    "cross_cats_sorted": [
      "cs.LG",
      "eess.SP"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2026-05-13T14:23:00Z",
    "title_canon_sha256": "a1552dc44d73c40b5fdf6ea1b93318c79cab22b0fb35be8a92443ffbca907b5c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13587",
    "kind": "arxiv",
    "version": 1
  }
}