Pith Number

pith:U2NLTI3V

pith:2026:U2NLTI3VIHKIITHEC3FRWH2HEI

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CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions

Chixiang Lu, Haibo Jiang, Hengyu Zhang, Jing Hao, Lifei Wang, Tianbo Liu, Xiaojuan Qi

CoRe-Gen generates molecular structures from mass spectra by training decoders on frequency-aware corrupted fingerprints to match real prediction noise.

arxiv:2605.12980 v1 · 2026-05-13 · cs.LG · cs.AI

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Claims

C1strongest claim

CoRe-Gen establishes a new state of the art on NPLIB1, achieving 19.54% Top-1 and 29.92% Top-10 exact-match accuracy, while remaining competitive on the more challenging MassSpecGym benchmark.

C2weakest assumption

The assumption that frequency-aware fingerprint corruption during training accurately reproduces the structured errors that arise from real spectrum-to-fingerprint predictors, and that the reported gains are not driven by benchmark-specific tuning or unstated data splits.

C3one line summary

CoRe-Gen reaches new state-of-the-art exact-match accuracy on the NPLIB1 benchmark for de novo molecular structure generation from mass spectra by using synthetic pretraining, frequency-aware corruption, and structure-aware decoding to close the gap between clean training data and noisy deployment.

References

43 extracted · 43 resolved · 0 Pith anchors

[1] Martin Alberts, Oliver Schilter, Fabio Zipoli, et al. 2024. Unraveling molecular structure: A multimodal spectroscopic dataset for chemistry.Advances in Neural Information Processing Systems, 37:12578 2024

[2] Felix Allen, Allison Pon, Michael Wilson, et al. 2014. CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra.Nucleic Acids Research, 42(W1):W9 2014

[3] Liu Cao, Mustafa Guler, Azat Tagirdzhanov, et al. 2021. MolDiscovery: learning mass spec- trometry fragmentation of small molecules.Nature Communications, 12(1):3718 2021

[4] Thomas Butler, Abraham Frandsen, Rose Lightheart, et al. 2023. MS2Mol: A transformer model for illuminating dark chemical space from mass spectra 2023

[5] Bushuiev, R., Bushuiev, A., de Jonge, N 2025

Receipt and verification

First computed	2026-05-18T03:09:08.589772Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a69ab9a37541d4844ce416cb1b1f47221170d06d0e8d1c8704292ceb190f0141

Aliases

arxiv: 2605.12980 · arxiv_version: 2605.12980v1 · doi: 10.48550/arxiv.2605.12980 · pith_short_12: U2NLTI3VIHKI · pith_short_16: U2NLTI3VIHKIITHE · pith_short_8: U2NLTI3V

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/U2NLTI3VIHKIITHEC3FRWH2HEI \
  | 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: a69ab9a37541d4844ce416cb1b1f47221170d06d0e8d1c8704292ceb190f0141

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "2467cf20fc0e7c927266b368b02b65dbf17599ea5ef2415712f7cb7583374923",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T04:22:55Z",
    "title_canon_sha256": "c1b6cdf4ca88296e08cb626fbc8a683c386c2efff5d04603b69c8f8d331d0d30"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12980",
    "kind": "arxiv",
    "version": 1
  }
}