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A conditional diffusion model can accurately extract TMD PDFs from raw SIDIS data, even in statistics-limited scenarios, revolutionizing how we approach parton distribution functions.
Iterative uncertainty correction allows for accurate parameter estimation in inverse problems, even with incomplete prior knowledge.
Jointly analyzing heterogeneous datasets with generative AI can yield precise estimates of unknowns that independent analyses miss, even under varying experimental conditions.
