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Transfer learning can unlock scalable emission control across diverse waste incineration plants by learning transferable system-level structures that capture physical constraints, operating-regime heterogeneity, and carbon-pollutant coupling.
Decoupling the "Thinker" from the "Editor" in image editing allows targeted optimization of reasoning, leading to performance competitive with strong proprietary models using a fixed generative model.
