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Rare Event Estimation via Iterative Unalignment

Paper recorded by Signals 4 on 2026-09-21 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.AI · 人工智能 · first seen 2026-09-22

Abstract

As agents are deployed with increased autonomy, even extremely rare events along their stochastic output trajectories can occur and prove catastrophic. Safe deployment therefore does not depend on whether these events can occur, but on how often they might. We study the problem of estimating the probability of rare events that arise from stochastic variation in the agent's own actions. Estimating

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#7 most recent of 340 cs.AI papers we have recorded · ↑ newer: DolphinBench: Mapping the Pareto Frontier of Agent Memory · ↓ older: Emergent Collusion in Long-Horizon LLM Agent Interaction
Cite this page: Rare Event Estimation via Iterative Unalignment: the #7 most recent of 340 cs.AI papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/rare-event-estimation-via-iterative-unalignment.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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