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Akụkọ ndị ọzọ
9 akụkọIhe ohuru ohuru
Paper introduces public AI benchmark for sorting shredded black industrial plastics
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.arxiv.orgIhe ohuru ohuru
Study finds apparent stroke-treatment gains from offline reinforcement learning are confounded
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.arxiv.orgIhe ohuru ohuru
Study finds anytime-valid AI monitors can repeatedly trigger on real forecast streams
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.arxiv.orgIhe ohuru ohuru
Paper proposes a two-step test for choosing LLMs under uncertain evaluations
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.arxiv.orgIhe ohuru ohuru
Paper proposes estimating how much of mixed text came from a watermarked AI model
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.arxiv.orgỤlọ ọrụ mmepụta ihe
Scientific Computing World reports iPronics raises $125 million for AI data centres
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.scientific-computing.comIhe ohuru ohuru
Paper updates a graph-neural-network model for predicting events across networks
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.arxiv.orgIhe ohuru ohuru
Paper proposes faster source-free adaptation for vision-language models
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%.arxiv.orgIhe ohuru ohuru
CommerceVibe turns e-commerce creative generation into editable HTML and CSS
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.arxiv.org
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