TurboAgent uses an LLM as coordinator for specialized agents to autonomously generate, predict, optimize, and validate turbomachinery designs, achieving R² > 0.91 agreement with CFD on a transonic compressor and 1.61% efficiency gains.
Autonomous microscopy experiments through large language model agents[J]
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
The paper proposes a four-role framework for LLMs in scientific innovation and reviews methods, benchmarks, and limitations across Assistant, Collaborator, Scientist, and Evaluator roles.
citing papers explorer
-
TurboAgent: An LLM-Driven Autonomous Multi-Agent Framework for Turbomachinery Aerodynamic Design
TurboAgent uses an LLM as coordinator for specialized agents to autonomously generate, predict, optimize, and validate turbomachinery designs, achieving R² > 0.91 agreement with CFD on a transonic compressor and 1.61% efficiency gains.
-
Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator
The paper proposes a four-role framework for LLMs in scientific innovation and reviews methods, benchmarks, and limitations across Assistant, Collaborator, Scientist, and Evaluator roles.