Generative AI translations in high-stakes emergency messaging
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arXiv:2610.08601v1 Announce Type: new Abstract: Emergency messaging such as extreme-weather reports and earthquake instructions can involve high stakes, to the extent that translation errors can lead...
arXiv:2610.32842v1 Announce Type: new Abstract: It is essential that we communicate with the entirety of an affected population during a crisis, including those who do not speak a region's dominant l...
arXiv:2607. 00019v1 Announce Type: cross Abstract: This paper offers a call to action.
arXiv:2602. 13452v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication.
The paper argues that as Large Language Models transition from chatbots to agentic systems, the current post-hoc interpretability paradigm is insufficient for safe deployment because it cannot audit or intervene before an output is produced. It proposes a shift to generative interpretability, where a model’s inference process inherently exposes semantically meaningful checkpoints that are human-understandable and can be causally intervened upon. The authors illustrate the advantages of this approach and introduce Neuro‑Symbolic Models as a concrete implementation.
arXiv:2601. 15828v4 Announce Type: replace-cross Abstract: This study investigates whether professional translators without prior specialized training can reliably identify short stories generated in Italian by artificial intelligence (AI).