Transformers without Normalization
Proposes a novel approach to training Transformers without normalization layers, using a technique called Dynamic Tanh (DyT) which effectively replace...
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Proposes a novel approach to training Transformers without normalization layers, using a technique called Dynamic Tanh (DyT) which effectively replace...
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Introduces CoSTA*, a novel cost-sensitive toolpath agent for multi-turn image editing, combining large language models (LLMs) and A* search to optimiz...
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Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automate...
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When developing tools for automated cortical segmentation, the ability to produce topologically correct segmentations is important in order to compute...
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Ex vivo MRI of the brain provides remarkable advantages over in vivo MRI for visualizing and characterizing detailed neuroanatomy. However, automated ...
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Introduces TPDiff, a temporal pyramid video diffusion model designed to enhance computational efficiency in video generation by optimizing frame rates...
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Intravascular ultrasound and optical coherence tomography are widely available for characterizing coronary stenoses and provide critical vessel parame...
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Presents STORM, a novel architecture for processing long video sequences in multimodal large language models (LLMs) by incorporating a temporal encode...
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MLGym is a novel framework and benchmark designed to evaluate and develop large language model (LLM) agents on diverse AI research tasks, providing a ...
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2D single-slice abdominal computed tomography (CT) enables the assessment of body habitus and organ health with low radiation exposure. However, singl...
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Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characteriza...
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Magnetic resonance imaging (MRI) is the non-invasive modality of choice for
body tissue composition analysis due to its excellent soft tissue contrast...
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