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原始数据层(AI 与用户都不会覆盖这些字段)
🌍 国际 政府/政策 AI 状态:已精选 综合价值 3.8 / 5
来源
arXiv 人工智能预印本(Atom)(arXiv · INTL)
发布时间
2026-10-02 23:33
采集时间
2026-10-06 06:58
语言
en
地域置信度
85%
原始链接
https://arxiv.org/abs/2610.03458v1
内容指纹
c95786d12054cecbf306936de61fccdccb3405df30fe2ee9bf9d61ce878623f6

AI 整理

分析于 2026-10-06 06:58(第 1 版,来源:offline)

Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for offline auditing.

为什么值得关注:属于政府/政策信息,对教育或研究方向可能产生影响

趋势标签: low hacking probe readout

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Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for offline auditing. We show that a low monitor readout does not identify whether such an intervention controls behavior. In a code-generation environment whose dominant exploit is available at the start of the reasoning trace, we train policies against three monitors that pass the same offline gate: an in-domain activation probe and two penalties conditioned on how early the policy commits to its own final answer. The probe score is at its numerical floor from the first recorded training step, and the trained-score median is zero for every prefix-trained run at the endpoint. These readouts estimate different quantities, and we do not compare their scales; within each monitor family, however, low values do not establish behavioral control. Within one fixed configuration, prefix-trained runs with the same zero-median trained score range, by seed alone, from a mixed regime with a low hacking share to near-pure reward hacking. All probe runs reach the hacking regime, but their floor-level readout reflects a mismatch between the position where the probe was validated and the position where it was read during training, not a second instance of this ambiguity. Text-level analysis identifies a prefix failure mode: generic planning and filler shells postpone the exploit past the cut without eliminating it from the final output. Low measured commitment therefore does not distinguish a low hacking share from delayed commitment to the exploit. Offline discrimination and low monitor-aligned readouts are insufficient evidence of behavioral control; an out-of-band behavioral check is required. We characterize the endpoint readout, not its evolution. Code is available at https://github.com/zhezhou1106/spoof-cost.

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2026-10-02 首次出现
A Near-Zero Monitor Readout Is Not Evidence of Behavioral Control

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