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  1. arXiv

    Multi-bit LLM watermarks can be rewritten without the key: a few accounts are enough to pin a text on someone else

    A multi-bit LLM watermark's account identifier can be displaced without the secret key: an attacker with a few accounts of its own can make the decoder read a text as belonging to a different account.

  2. arXiv

    Selfish robotaxis shave their own commutes but add 1.7% to human drivers; a social cost term cuts that to 1.1%

    On real road networks, autonomous vehicles that minimize only their own travel time raise human-driven vehicles' average travel time, because road capacity is shared and the routes that avoid congestion shift cost onto others. The study adds a marginal cost term to the autonomous vehicle reward: a counterfactual simulation removes that vehicle from the network and compares the remaining vehicles' travel times, quantifying its system impact. On the real networks of Ingolstadt and Provins, the social term cuts the increase in human travel time from 1.7% to 1.1% while autonomous vehicles also get faster; computing marginal cost for only about 40% of the most impactful vehicles reduces extra simulations from roughly 4.14 million to about 2.46 million with close performance.

  3. The added value of echocardiography in pulmonary arterial hypertension risk assessment: an artificial intelligence machine learning-derived analysis of the ULTRA RIGHT VALUE registry

    In a 401-patient multicentre European prospective pulmonary arterial hypertension (PAH) cohort, adding right ventricular echocardiographic parameters—especially right ventricular-pulmonary arterial (RV-PA) coupling indices—to the ESC/ERS and REVEAL 2.0 risk scores improved the c-index for morbi-mortality prediction from 0.73 to 0.78 and from 0.74 to 0.79, respectively (P<0.01), with machine learning identifying RV-PA coupling as the most influential dimension.

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