Pith Number

pith:TMX3AMVO

pith:2026:TMX3AMVOXGR2BWJ563UMYWTVZX

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JI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification

Dat Cao, Hien Chu, Hien Kha, Minh Le, Nguyen Quoc Khanh Le, Phan Nguyen, Trang Pham

JI-ADF integrates joint-individual learning and adaptive decision fusion for improved multimodal skin lesion classification.

arxiv:2604.27343 v2 · 2026-04-30 · cs.CV

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\pithnumber{TMX3AMVOXGR2BWJ563UMYWTVZX}

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Record completeness

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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

The proposed JI-ADF method demonstrates strong and well-balanced performance across lesion categories on the MILK10k benchmark, improving sensitivity and Dice score while maintaining high specificity and good calibration.

C2weakest assumption

That the MILK10k benchmark faithfully represents real-world clinical acquisition conditions and severe class imbalance, and that the observed improvements arise from the joint-individual learning and adaptive fusion rather than dataset-specific tuning or implementation details.

C3one line summary

JI-ADF fuses three modalities with adaptive decision fusion and a multimodal attention module to achieve balanced, well-calibrated performance on the imbalanced MILK10k skin lesion benchmark.

Receipt and verification

First computed	2026-06-05T01:15:24.989914Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9b2fb032aeb9a3a0d93df6e8cc5a75cdf9d05e736ae5230370a6caf1355a9f57

Aliases

arxiv: 2604.27343 · arxiv_version: 2604.27343v2 · doi: 10.48550/arxiv.2604.27343 · pith_short_12: TMX3AMVOXGR2 · pith_short_16: TMX3AMVOXGR2BWJ5 · pith_short_8: TMX3AMVO

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/TMX3AMVOXGR2BWJ563UMYWTVZX \
  | 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: 9b2fb032aeb9a3a0d93df6e8cc5a75cdf9d05e736ae5230370a6caf1355a9f57

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "54916431b22949e07db7f5e9f079d0dbb803bf496e9a3110d2e88fc8291c7a45",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-30T02:48:15Z",
    "title_canon_sha256": "1fc31c2b4603452bb9f64a41eae7ef53c2ed8cc239a3905b61a5225f871ab92f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.27343",
    "kind": "arxiv",
    "version": 2
  }
}