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A new preprint proposes evaluating video world models with 3D reconstruction and task-oriented metrics, reporting that visual judgments can miss failures tied to state understanding and executable actions.
Researchers describe a machine-learning pipeline and public hyperspectral-imaging dataset designed to identify four polymers in shredded black plastic from end-of-life vehicles.
A 129,033-patient stroke registry study found that offline reinforcement-learning policies appeared to outperform physician decisions, but the estimated improvement weakened substantially after researchers removed baseline-severity information embedded in the reward.
A new preprint reports that a statistical monitor behaved as expected on exchangeable synthetic data but fired in every tested clean run on five real forecasting streams, warning that deployment guarantees depend on assumptions that may fail in adaptive AI systems.
A new preprint argues that companies can sometimes certify the best assignment of large language models to recurring workloads even when model-quality estimates remain uncertain. It proposes a two-solve test and an evidence-gathering method called CASE.
A revised arXiv paper presents estimators for the share of watermarked language-model content in text that combines human and AI writing, while showing that some watermarking schemes cannot support reliable proportion estimates.
Scientific Computing World reports that iPronics raised $125 million in Series B funding to support commercial deployment of its programmable optical switching technology and expand its U.S. operations.
A revised research paper presents a point-process model that uses graph neural networks to represent how past events influence future events across networked systems.
A new preprint proposes DSSG-PAC, a method for adapting vision-language models without source data or task-specific source models. The authors report that it largely preserves adaptation performance while reducing total adaptation time by 18.9%.
A new preprint describes CommerceVibe, an AI system that generates editable e-commerce creatives as executable HTML and CSS code. Its authors report a weighted benchmark score of 94.0, up from 87.3 for a supervised-fine-tuning-only version, with additional validation from five design experts.
Complete Music Update reports that Universal Music and Sony Music filed an amended copyright complaint against AI music company Suno after a judge allowed them to add allegations that Suno obtained training recordings through stream ripping.
An arXiv preprint reports that simulated automatic speech-recognition errors can make embodied AI systems more likely to accept harmful instructions, generate unsafe plans and execute them in benchmark scenarios.
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