Pith Number

pith:W33V37AP

pith:2026:W33V37APE3EILLZT7BY3HRCM5T

not attested not anchored not stored refs resolved

Physics-Grounded Adversarial Stain Augmentation with Calibrated Coverage Guarantees

Mingi Hong

CASA performs adversarial augmentation in Macenko stain space with DKW-calibrated budgets to cover unseen hospital variations.

arxiv:2605.13889 v1 · 2026-05-12 · eess.IV · cs.CV · cs.LG

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\usepackage{pith}
\pithnumber{W33V37APE3EILLZT7BY3HRCM5T}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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

On Camelyon17-WILDS (5 seeds), CASA achieves 93.9% ± 1.6% slide-level accuracy -- outperforming HED-strong (88.4% ± 7.3%), RandStainNA (85.2% ± 6.7%), and ERM (63.9% ± 11.3%) -- with the highest worst-group accuracy (84.9% ± 0.9%) among all 10 compared methods.

C2weakest assumption

That calibrating an adversarial budget from multi-center statistics via the DKW inequality in Macenko space supplies coverage guarantees for truly unseen centers without post-hoc tuning or access to target-domain data.

C3one line summary

CASA achieves 93.9% slide-level accuracy on Camelyon17-WILDS by adversarially augmenting stains in Macenko space with DKW-calibrated coverage, outperforming baselines including in worst-group accuracy.

References

10 extracted · 10 resolved · 0 Pith anchors

[1] Medical Image Analysis , volume= 2019

[2] IEEE International Symposium on Biomedical Imaging (ISBI) , pages= 2009

[3] Shen, Yiqing and Luo, Yulin and Shen, Dinggang and Ke, Jing , booktitle=. 2022 , publisher= 2022

[4] Zheng, Guangtao and Huai, Mengdi and Zhang, Aidong , booktitle=

[5] Advances in Neural Information Processing Systems (NeurIPS) , year=

Receipt and verification

First computed	2026-05-17T23:39:19.087274Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

b6f75dfc0f26c885af33f871b3c44cece13cbd063d7e703ad319c2364209bb7b

Aliases

arxiv: 2605.13889 · arxiv_version: 2605.13889v1 · doi: 10.48550/arxiv.2605.13889 · pith_short_12: W33V37APE3EI · pith_short_16: W33V37APE3EILLZT · pith_short_8: W33V37AP

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/W33V37APE3EILLZT7BY3HRCM5T \
  | 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: b6f75dfc0f26c885af33f871b3c44cece13cbd063d7e703ad319c2364209bb7b

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "5f2ec9be856243d7a3a380e68a03cb487e0eaff6fd8ce300a306e69536ad9fa8",
    "cross_cats_sorted": [
      "cs.CV",
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "eess.IV",
    "submitted_at": "2026-05-12T04:39:33Z",
    "title_canon_sha256": "fe70c1e278ec032eeea4ea3c84bf1e6d33d296fe0dbec349c0650448561c5910"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13889",
    "kind": "arxiv",
    "version": 1
  }
}