A multi-agent LLM system with retrieval and local code execution reproduced ACT DR6 lensing cosmological parameter constraints without human-written code, and generalized to two research-software tasks.
AstroMLab 3: Achieving GPT-4o Level Performance in Astronomy with a Specialized 8B-Parameter Large Language Model
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abstract
AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, cosmology, and astronomical instrumentation. Trained on the complete collection of astronomy-related arXiv papers from 2007 to 2024 along with millions of synthetically-generated question-answer pairs and other astronomical literature, AstroSage-Llama-3.1-8B demonstrates remarkable proficiency on a wide range of questions. AstroSage-Llama-3.1-8B scores 80.9% on the AstroMLab-1 benchmark, greatly outperforming all models -- proprietary and open-weight -- in the 8-billion parameter class, and performing on par with GPT-4o. This achievement demonstrates the potential of domain specialization in AI, suggesting that focused training can yield capabilities exceeding those of much larger, general-purpose models. AstroSage-Llama-3.1-8B is freely available, enabling widespread access to advanced AI capabilities for astronomical education and research.
fields
astro-ph.IM 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
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Multi-Agent System for Cosmological Parameter Analysis
A multi-agent LLM system with retrieval and local code execution reproduced ACT DR6 lensing cosmological parameter constraints without human-written code, and generalized to two research-software tasks.