Pith Number

pith:PLRYCHO4

pith:2026:PLRYCHO4Z2VCF5C2NIVNH5TQSQ

not attested not anchored not stored refs pending

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration

Cong Cong, Luru Jing, Yanyuan Chen, Yongzhi Cao

Local Gaussian-mixture alignment of synthetic features lets pathology institutions train models together without exchanging parameters.

arxiv:2605.00578 v2 · 2026-05-01 · cs.CV

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\usepackage{pith}
\pithnumber{PLRYCHO4Z2VCF5C2NIVNH5TQSQ}

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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

Experiments on TCGA-IDH, CAMELYON16, and CAMELYON17 show that FedHD consistently outperforms state-of-the-art federated and distillation baselines.

C2weakest assumption

The one-to-one distillation strategy and curriculum integration preserve diagnostic diversity and produce net positive transfer without introducing distribution shift that harms local performance.

C3one line summary

FedHD performs federated distillation for whole slide images by generating one synthetic feature set per real slide via Gaussian-mixture alignment and adding them via curriculum integration, outperforming prior federated and distillation methods on TCGA-IDH, CAMELYON16, and CAMELYON17.

Receipt and verification

First computed	2026-05-20T01:05:14.916965Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7ae3811ddcceaa22f45a6a2ad3f67094277b267eab72df81a3169626bddad616

Aliases

arxiv: 2605.00578 · arxiv_version: 2605.00578v2 · doi: 10.48550/arxiv.2605.00578 · pith_short_12: PLRYCHO4Z2VC · pith_short_16: PLRYCHO4Z2VCF5C2 · pith_short_8: PLRYCHO4

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/PLRYCHO4Z2VCF5C2NIVNH5TQSQ \
  | 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: 7ae3811ddcceaa22f45a6a2ad3f67094277b267eab72df81a3169626bddad616

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "5f653a6c5d66344cc677a1a848347d09b2999f2c7be8a202c1525f2466007760",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-01T11:25:54Z",
    "title_canon_sha256": "9408389073019808ca8948d01fb7d1480d6e3c2e893dfa02d1a45fbf5cd2c78e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.00578",
    "kind": "arxiv",
    "version": 2
  }
}