ADAPT for Science: A Multi-Agent System for Self-Evolving Scientific Optimization
3.60T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2610.30851.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryADAPT for Science is a multi-agent framework that splits scientific optimization into where-to-search and how-to-search decisions. Evaluated on gravitational wave detector design via a differentiable physics simulator across eight unseen topologies, it cuts mean loss by 54.9% over the best classical optimizer and 62.2% over the best general agentic baseline.
Why it mattersConcrete multi-agent system with quantified gains on a hard scientific design task under tight evaluation budgets, showing how agentic structure can outperform both classical and general-purpose evolutionary baselines.
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