谁在推动前沿？开放前沿挑战在身份免费时的支付机制分析
Who Moved the Frontier? Paying Open Frontier Challenges with Free Identities
AI 导读
arXiv 论文分析开放前沿挑战在身份免费可注册时如何设计支付规则。作者发现排名奖励可被多人身份操纵：重放某挑战的一条赛道时，同一求解者用两个身份可分获第一、第二名。论文证明预测市场式规则——按每步新增进展付费——在精确分数下可抵抗拆分合并操作，并针对噪声分数提出按次收费、反悔版税等机制，还对五个公开挑战给出规则建议。
正文 · 原文
Abstract:In an open frontier challenge, anyone, person or AI agent, submits changes to a shared problem, and a change that beats the best measured score becomes the public baseline. How should it pay when identities are free? Rank prizes can be gamed: on a replay of one track of a recent challenge, one solver's steps under two identities would have taken first and second prize. We consider a prediction-market rule, proposed for machine-learning contests, that pays each accepted step for the progress it adds; with exact scores, among rules that see only a step's start and end, only these resist splitting and merging, and extra identities gain nothing. With noisy scores and independent normal runs, we prove that any payment that never takes money back and pays real improvements also pays something, on average, to a change that does nothing. We propose a fee per submission, at least what luck pays per attempt, that removes each attempt's expected profit if verifiers are honest and no submission is noisier than planned; nothing enforces that bound, and under noise the rule does not cap the total paid. If crediting another and faking credit to one's second account look the same, a rule that neither rewards fakes nor punishes honesty pays for credit at most what lying costs. We introduce a royalty on how much a later gain falls without the earlier change, which needs no claims but needs removable changes. For five public challenges, we name the rule our results would support.
| Subjects: | Computer Science and Game Theory (cs.GT); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2611.14974 [cs.GT] |
| (or arXiv:2611.14974v1 [cs.GT] for this version) | |
| https://doi.org/10.48550/arXiv.2611.14974 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Luca Zanolini [view email]
[v1]
Wed, 11 Nov 2026 03:34:51 UTC (78 KB)
来源：arXiv cs.AI · arxiv.org