Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination
Paper • 2607.00924 • Published • 10
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AstroMLab is a collaborative initiative of astronomers and AI experts dedicated to advancing Large Language Models in astronomy. Our goal is to expedite scientific discovery through LLM-driven research.
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Sand33p
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A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Paper • 2301.07799 • Published
AstroMLab 1: Who Wins Astronomy Jeopardy!?
Paper • 2407.11194 • Published
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Paper • 2411.15221 • Published • 30
EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants
Paper • 2502.20309 • Published
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
Paper • 2312.03876 • Published
AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions
Paper • 2509.13523 • Published • 7
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