SIGA: Self-Evolving Coding-Agent Adapters for Scientific Simulation

📰 ArXiv cs.AI

arXiv:2606.09774v1 Announce Type: new Abstract: Advanced scientific simulators expose specialized input languages that turn simulation goals into executable configurations, but learning them can cost domain scientists hours to days. We study simulator setup as a problem of agent-tool interface grounding: what minimal simulator-specific adaptations are needed for an off-the-shelf coding agent to operate real scientific software? Our intuition is that coding agents already know how to navigate fil

Published 9 Jun 2026
Read full paper → ← Back to Reads