Empirical comparison of domain-specific, computer-use, and general-purpose LLM agents plus CLI/GUI modalities on SciVis tasks reveals general-purpose agents highest in success rate but costliest, domain-specific agents more efficient, and persistent memory beneficial depending on mode.
In: Pro- ceedings of the SC ’25 Workshops of the International Conference for High Perfor- mance Computing, Networking, Storage and Analysis
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CoVer extended to Fortran preserves analysis accuracy, reveals a bug in MPI-BugBench, and runs substantially faster than MUST while supporting multiple languages.
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Exploring LLM Agent Designs and Interaction Modalities for Scientific Visualization
Empirical comparison of domain-specific, computer-use, and general-purpose LLM agents plus CLI/GUI modalities on SciVis tasks reveals general-purpose agents highest in success rate but costliest, domain-specific agents more efficient, and persistent memory beneficial depending on mode.