AINeutralarXiv – CS AI · May 16/10
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Exploring Interaction Paradigms for LLM Agents in Scientific Visualization
Researchers evaluated eight LLM agents across three interaction paradigms—domain-specific agents, computer-use agents, and general-purpose coding agents—on scientific visualization tasks. The study reveals fundamental tradeoffs: general-purpose agents excel at task completion but consume more computational resources, while domain-specific agents offer efficiency and stability at the cost of flexibility, with persistent memory improving performance across modalities.