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Reducing model storage by nearly 10% without sacrificing rendering quality, 3DGBGS redefines efficiency in novel-view synthesis.
Domain-specific reasoning and tool coordination in materials science no longer require massive LLMs: a lightweight, dual-model agent outperforms larger general-purpose models while slashing hardware costs.
Square superpixels, generated via granular ball computing, unlock efficient parallel processing and end-to-end optimization in deep learning pipelines by replacing irregular shapes with multi-scale square blocks.
