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pith:QZAS27HM

pith:2026:QZAS27HMI66A6OKTKFIELELYG6
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QUIVER: Cost-Aware Adaptive Preference Querying in Surrogate-Assisted Evolutionary Multi-Objective Optimization

Florian A. D. Burnat

QUIVER adaptively chooses between objective evaluations and two types of preference queries to maximize expected decision quality gain per unit cost, reaching 25% lower final utility regret than fixed strategies on hard benchmarks.

arxiv:2605.04267 v2 · 2026-05-05 · cs.LG · cs.NE · math.OC

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\pithnumber{QZAS27HMI66A6OKTKFIELELYG6}

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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
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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

QUIVER achieves the lowest final utility regret on challenging WFG problems (utility regret of 2.14 on WFG4, 2.82 on WFG9: a 25% improvement over baselines), outperforming all single-modality baselines.

C2weakest assumption

The synthetic decision-maker models used to simulate preference responses and costs accurately represent real human behavior and query costs in the target application domains.

C3one line summary

QUIVER adaptively balances cheap pairwise preference queries and costly indifference adjustments with objective evaluations to achieve lower utility regret than single-modality baselines on WFG benchmarks.

Formal links

3 machine-checked theorem links

Receipt and verification
First computed 2026-06-19T16:11:24.098368Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

86412d7cec47bc0f3953515045917837a90ebfeec9614f49d1d5133e739b94f0

Aliases

arxiv: 2605.04267 · arxiv_version: 2605.04267v2 · doi: 10.48550/arxiv.2605.04267 · pith_short_12: QZAS27HMI66A · pith_short_16: QZAS27HMI66A6OKT · pith_short_8: QZAS27HM
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QZAS27HMI66A6OKTKFIELELYG6 \
  | 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: 86412d7cec47bc0f3953515045917837a90ebfeec9614f49d1d5133e739b94f0
Canonical record JSON
{
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    "abstract_canon_sha256": "9d9104f151f74875fd6637a864a303ae3bf95fa83af08e30f246fd798a563b2a",
    "cross_cats_sorted": [
      "cs.NE",
      "math.OC"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-05T20:02:35Z",
    "title_canon_sha256": "126b99590e010d4c1ebac317cce7bdd126a7281a79142dc6ab77180e6aaee1eb"
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  "source": {
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    "kind": "arxiv",
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