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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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this direction for LLM-augmented data processing. They show that the execution of LLM-based workflows raises new optimization problems, since cost, latency, and output quality depend on the choice and organization
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natural language. MARIANNE is an Inria joint project-team with the I3S (Computer Science) laboratory of Université Côte d’Azur and CNRS. The team is composed of computer scientists, but it holds a strong
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order to leverage information contained in GNSS data. We will follow the same procedure than with PEGS: simulating synthetic GNSS records corresponding to an exhaustive set of possible earthquake
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
. These approaches allow for precise simulations of fluid mechanics applied to physiological processes, contributing to a better understanding of diseases and the development of innovative medical technologies