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University of Notre Dame
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Achieving zero bit-error rates in volumetric data representation could revolutionize how we handle scientific visualizations and analyses.
EVOLVE achieves unprecedented compression ratios while maintaining high reconstruction quality, setting a new standard for volumetric data compression in scientific simulations.
ECoNGS achieves a remarkable 6.1x reduction in model size while enhancing reconstruction quality by up to 2.2 dB, revolutionizing volume visualization efficiency.
Current multimodal language models falter in scientific visualization literacy, with only Gemini surpassing human performance in select areas.
General-purpose coding agents may ace scientific visualization tasks, but their computational cost is a steep price compared to the efficiency of domain-specific agents, highlighting a crucial trade-off in LLM agent design.
