A multimodal 3D foundation model pretrained on LSM volumes via masked reconstruction and image-text alignment enables improved few-shot segmentation, classification, and deblurring.
Same pre-training loss, better downstream: Implicit bias matters for language models, 2022
2 Pith papers cite this work. Polarity classification is still indexing.
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Self-generated replay from language models nearly eliminates catastrophic forgetting during finetuning except when models are pretrained close to saturation.
citing papers explorer
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A Multimodal 3D Foundation Model for Light Sheet Fluorescence Microscopy Enables Few-Shot Segmentation, Classification, and Deblurring
A multimodal 3D foundation model pretrained on LSM volumes via masked reconstruction and image-text alignment enables improved few-shot segmentation, classification, and deblurring.
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Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay
Self-generated replay from language models nearly eliminates catastrophic forgetting during finetuning except when models are pretrained close to saturation.