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pith:DPQ22QU6

pith:2026:DPQ22QU65CCC35XGTUC3WCVQJP
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An Axiomatic Benchmark for Evaluation of Scientific Novelty Metrics

ChengXiang Zhai, Miri Liu

No single metric satisfies all axioms for scientific novelty, but combining complementary architectures reaches 90.1 percent compliance.

arxiv:2604.15145 v2 · 2026-04-16 · cs.AI · cs.DL

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\pithnumber{DPQ22QU65CCC35XGTUC3WCVQJP}

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3 Author claim open · sign in to claim
4 Citations open
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Claims

C1strongest claim

Combining metrics of complementary architectures leads to consistent improvements on the benchmark, with per-axiom weighting achieving 90.1% versus 71.5% for the best individual metric.

C2weakest assumption

The axioms defined capture the essential aspects of human scientific norms for novelty, and the ten tasks across three AI domains sufficiently represent the general problem of evaluating scientific novelty.

C3one line summary

An axiomatic benchmark shows no single novelty metric satisfies all desired properties consistently, but combining complementary metrics reaches 90.1% performance versus 71.5% for the best individual metric.

Receipt and verification
First computed 2026-08-07T00:45:50.713682Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

1be1ad429ee8842df6e69d05bb0ab04bf8a1b317054782e7c1918eaaed45c728

Aliases

arxiv: 2604.15145 · arxiv_version: 2604.15145v2 · doi: 10.48550/arxiv.2604.15145 · pith_short_12: DPQ22QU65CCC · pith_short_16: DPQ22QU65CCC35XG · pith_short_8: DPQ22QU6
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/DPQ22QU65CCC35XGTUC3WCVQJP \
  | 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: 1be1ad429ee8842df6e69d05bb0ab04bf8a1b317054782e7c1918eaaed45c728
Canonical record JSON
{
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    "cross_cats_sorted": [
      "cs.DL"
    ],
    "license": "http://creativecommons.org/licenses/by-sa/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-04-16T15:19:58Z",
    "title_canon_sha256": "216e4c00bf4aa30bae8db2a97ac360162f870f288d5668cc136ced87ce5f7431"
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