Large text-to-video models trained on internet-scale data have shown extraordinary capabilities to generate high-fidelity films from arbitrarily written descriptions. However, fine-tuning a pretrained huge model might be prohibitively expensive, making it difficult to adapt these models...
Researchers have proposed a novel approach to enforcing distributional constraints in machine learning models using multi-marginal optimal transport. This approach is designed to be computationally efficient and allows for efficient computation of gradients during backpropagation.
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