AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow explores An LLM-driven multi-agent framework that enables domain scientists to autonomously build high-quality deep learning surrogate models for subsurface flow simulations using natural language.. Commercial viability score: 8/10 in AI for Science.
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Canonical ID autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsu | Route /paper/autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsu
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curl https://sciencetostartup.com/api/v1/agent-handoff/paper/autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsuMCP example
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/buildability/autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsu
Subject: AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow
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Dimensions overall score 8.0
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This equation captures one of the core mathematical components of the system. log-normal distribution, with the mean of log-permeability (log π) being 2.5 and the standard deviation of log πbeing
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Receipt path
/buildability/autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsu
Paper ref
autosurrogate-an-llm-driven-multi-agent-framework-for-autonomous-construction-of-deep-learning-surrogate-models-in-subsu
arXiv id
2604.11945
Generated at
2026-04-15T16:42:15.014Z
Evidence freshness
stale
Last verification
2026-04-15T16:42:15.014Z
Sources
3
References
0
Coverage
50%
Lineage hash
83b4ac2a926a435cd4e33152385bcca4ad23e20ee76e3f3c58affe995ddac588
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unsigned_external
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not_verified
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Pending verification refs / 3 sources / Verification pending
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references
This equation captures one of the core mathematical components of the system. m) and 15 m in z direction (ππ§= 15 m). The standard Gaussian realizations of log πare generated with the Stanford
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. The correlation length of log-permeability (log π) fields is set to be 3600 m in x and y directions (ππ₯= ππ¦=
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