False Reassurance in LLM Severe-Weather Guidance: A Replayable Evaluation Against Real NWS Alerts
Paper recorded by Signals 4 on 2026-11-03 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-11-03 on arXiv · recorded by Signals 4 on 2026-11-04
Category: cs.AI · 人工智能 · first seen 2026-11-04
Abstract
An LLM assistant that cannot see official severe-weather alerts may tell users that conditions are calm while a warning is active. We call this false reassurance and measure it by replaying 117 frozen cases built from real U.S. National Weather Service (NWS) alerts (69 alert cases, 32 no-alert controls, 16 non-U.S. locations) through five conditions of a Claude-based preparedness pipeline that dif
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Cite this page: False Reassurance in LLM Severe-Weather Guidance: A Replayable Evaluation Against Real NWS Alerts: the #14 most recent of 920 cs.AI papers we have recorded (as of 2026-11-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/false-reassurance-in-llm-severe-weather-guidance-a-replayable-evaluation-against.html
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